But history shows the biggest early profits often come from somewhere else entirely – the bottlenecks.

In today’s Friday Digest takeover, our macro investing expert Eric Fry revisits a little-remembered dynamic from the dot-com era. While everyone was chasing internet stocks, a quiet supply crunch in key industrial metals created massive gains for mining companies supplying the infrastructure behind that boom.

Eric believes we may be seeing a similar pattern emerge today. The AI revolution requires enormous amounts of critical materials. When demand outruns supply, bottlenecks form – and the companies controlling those choke points can become some of the market’s biggest winners.

Today, Eric walks through several historical examples to explain why the same forces may now be forming across the AI supply chain.

He’ll also be breaking down this opportunity in far greater detail during his free FutureProof 2026 event on March 18 at 1 p.m. ET. He’ll reveal 15 companies positioned to benefit from the next wave of AI bottlenecks. You can reserve your spot right here.

If you want a head start on where the next wave of AI winners will be coming from, today’s Digest takeover is for you.

I’ll let Eric take it from here.

Have a good evening,
Jeff Remsburg

People took out thousands of dollars in cash in fear that ATMs wouldn’t work.

Thousands canceled flights because they believed planes might simply fall out of the sky.

Stores across the globe sold out of generators, bottled water, and cans of Spam.

For younger folks, it may sound crazy, but the panic over the so-called Y2K bug was very real.

At the turn of the millennium, people around the world feared computers would crash on January 1, 2000 — misreading the “00” date as 1900 instead of 2000.

The problem was real. And real money was spent to solve it.

The Clinton administration said in December 1999 that preparing the U.S. for Y2K was probably “the single largest technology management challenge in history.”

Researchers at Gartner estimate the global cost of Y2K remediation — across governments and private companies — totaled between $300 billion and $600 billion.

In the end, the remediation worked. Aside from a few minor glitches (and perhaps a lingering surplus of canned Spam), the world’s technology systems continued running smoothly.

But while the public worried about computers crashing…

… another problem was quietly forming behind the scenes.

We had to move so quickly at the turn of the century largely because of the tech boom leading up to it.

The dot-com surge triggered a massive buildout of internet infrastructure, and that buildout required enormous quantities of raw materials.

So while consumers were stockpiling supplies…

… tech companies were scrambling to secure metals.

During the late 1990s and early 2000s, the tech boom triggered a surge in demand for critical materials used in electronics and networking equipment:

• Copper – to carry electricity and data
• Tin – used in electronic soldering
• Gold – used in corrosion-resistant connectors
• Rare earth elements – used in disk drives, displays, and fiber optics

The explosion of internet infrastructure, personal computers, and networking hardware meant the world suddenly needed far more metals than usual.

But mining and refining capacity couldn’t expand overnight.

The result was a classic supply bottleneck.

Prices for semiconductors and other hardware spiked. Companies like Cisco Systems Inc. (CSCO), Intel Corp. (INTC), and Dell Technologies Inc. (DELL) faced growing lead-time issues that slowed product rollouts.

But this metals shortage also created hidden investment opportunities.

Investors who anticipated which resources would become scarce had the chance to profit in extraordinary ways, much like investors who recently benefited from Nvidia Corp.’s (NVDA) nearly 1,000% gains during the AI compute bottleneck.

From 1998 to 2001, I recommended four mining stocks to my readers that went on to generate remarkable gains. These companies became the quiet winners of the late-1990s tech boom.

Today, let’s take a closer look at them — and how identifying a supply bottleneck early created enormous upside.

Then I’ll show you how this same profit-making “bottleneck” cycle is unfolding again thanks to AI… and where investors still have time to position themselves.

Let’s take a look…

When the Internet Needed Copper

Back during the dot-com era, Antofagasta plc (ANTO.L) was not yet the global copper giant it is today.

In the mid-1990s, the company was still a diversified Chilean holding company involved in railways, finance, and industrial businesses.

But in 1996, Antofagasta spun off many of its non-mining assets into Quiñenco SA, one of Chile’s largest conglomerates.

That move transformed Antofagasta into a copper-focused mining company — just as the internet boom was beginning to drive enormous demand for the metal.

During the late 1990s, the company began developing the massive Los Pelambres copper mine in Chile’s Coquimbo Region. Construction started in 1997. Initial production began in 1999. By 2001, the mine had reached full capacity.

Los Pelambres quickly transformed Antofagasta from a relatively small mining group into a major global copper producer. In the early 2000s, the mine accounted for roughly three-quarters of the company’s revenue.

I recommended Antofagasta to my readers on December 18, 1998 — about a year before the mine began production.

Over the next three years, the stock soared 205%, while the S&P 500 was essentially flat.

Over six years, Antofagasta delivered an astonishing 633% gain, while the S&P actually lost money.

Antofagasta built capacity during the investment phase of the 1990s, and then benefited enormously once the metals bottleneck tightened.

But it wasn’t the only copper producer positioned to win.

While tech companies were building the internet, companies like Freeport-McMoRan Inc. (FCX) were supplying the physical materials that made the digital world possible.

Freeport’s crown jewel was the Grasberg Mine in Indonesia, one of the most important copper and gold mines on Earth.

Because Grasberg was already operating at scale, Freeport could immediately ramp up production as demand surged. The company didn’t need to build new capacity to benefit from the bottleneck — it simply needed to keep producing.

I recommended Freeport to my readers on April 26, 1999.

Over the next three years, the stock rose 37%, while the S&P 500 dropped 17%.

Over six years, Freeport climbed 154%, while the broader market lost 10%.

Copper wasn’t the only opportunity of the time…

The Other Metals That Made Investors Rich

During the late 1990s, Cameco Corp. (CCJ) controlled some of the richest uranium deposits in the world in Canada’s Athabasca Basin.

Its McArthur River and Key Lake mines had extremely high uranium grades, giving Cameco some of the lowest production costs in the entire industry.

Now, uranium wasn’t central to the internet infrastructure buildout. Prices were relatively weak during most of the dot-com era. So you might wonder why Cameco belongs on this list.

The answer is simple: cost advantage. Because its deposits were so rich, Cameco remained profitable even during periods of weak uranium prices.

Then, shortly after the dot-com era ended, uranium experienced its own supply crunch. And Cameco was perfectly positioned to benefit.

I recommended the company to my readers on July 9, 1999.

Over three years, the stock rose 36%, while the S&P 500 declined by nearly 30%.

Over six years, Cameco climbed 221% as the S&P fell 15%.

My final bottleneck winner came from another corner of the mining world.

Impala Platinum Holdings (IMPUY) was one of the largest producers of platinum-group metals in the world.

These metals — platinum, palladium, rhodium, iridium, and osmium — are used in:

• automotive catalytic converters
• electronics components
• chemical processing
• petroleum refining

During the late 1990s, demand for these metals increased sharply as global manufacturing expanded. Meanwhile, tightening emissions standards increased demand for catalytic converters.

The price of platinum surged from roughly $350–$400 per ounce to more than $600. Because Impala was already a major supplier, those rising prices flowed straight into the company’s profits.

I recommended Impala on March 30, 2001.

Over the following three years, the stock rose 176%, compared to just 2% for the S&P 500.

Over six years, Impala soared 649%, while the S&P gained only 22%.

The lesson is clear.

During major tech booms, materials and infrastructure often become bottlenecks.

And the companies that control those bottlenecks can generate extraordinary returns.

Where the Next Bottleneck Is Forming

Today, we’re seeing something very similar unfold during the AI Revolution.

Artificial intelligence requires enormous quantities of infrastructure, including chips, electricity, memory, and critical metals.

And whenever demand for infrastructure rises faster than supply can respond, bottlenecks emerge.

For investors who identify them early, the upside can be highly asymmetric.

In general, I look for four things:

Of course, identifying these bottlenecks in real time is easier said than done.

But right now, several new constraints are beginning to appear across the AI supply chain.

And the companies positioned to solve those constraints could become some of the biggest winners of the next phase of the AI boom.

That’s exactly what I’ll be discussing in much greater detail during FutureProof 2026, happening Wednesday, March 18 at 1 p.m. ET.

During this free broadcast, I’ll explain why new shortages in metals, electricity, and memory could soon become the next major bottlenecks in the AI Revolution.

I’ll also reveal 15 companies already positioned to benefit from these developing constraints.

If history is any guide, the next Nvidia Corp. (NVDA)-style winner may not come from AI software — but from the companies solving AI’s biggest infrastructure challenges.

You can reserve your spot here.

Regards,

Eric Fry

Editor, The Speculator

P.S. Eric has spent decades studying the kinds of market cycles he describes above — and few analysts I know are better at identifying these “bottleneck” opportunities early. That’s exactly what he plans to show during FutureProof 2026 on March 18 at 1 p.m. ET, where he’ll walk through the next major bottlenecks forming in the AI economy — and the companies positioned to benefit. You can reserve your free spot here.

The post The Next Nvidia May Come From This Industry appeared first on InvestorPlace.

My colleague Eric Fry has been studying these constraints closely. As editor of The Speculator, Eric has built a reputation for identifying major technological and economic shifts early – often before Wall Street fully recognizes them.

In the guest essay below, Eric explains how the first major bottleneck of the AI boom – a shortage of computing power – helped drive huge gains for companies like NVIDIA and Broadcom. More importantly, he explains why that was likely only the beginning.

Next Wednesday, Eric will expand on this idea during a free online presentation called FutureProof 2026, where he’ll walk through several emerging infrastructure bottlenecks that could shape the next phase of the AI boom. (You can reserve your spot for that event here.) For now, take a look at Eric’s essay below.

**

In November 2023 – just a year after ChatGPT’s debut – OpenAI CEO Sam Altman made a surprising decision.

He stopped taking new customers.

New signups for ChatGPT’s paid subscriptions were suddenly suspended. Anyone hoping to access OpenAI’s most advanced models was simply turned away.

This wasn’t because demand had collapsed.

It was because demand had exploded. In its first year, ChatGPT reached 100 million weekly active users. And after its first developers conference on November 6, 2023 – where the company unveiled ChatGPT Plus – the number of wannabe subscribers surged rapidly.  

Just a week later, Altman literally had to start turning away folks with credit cards in hand.

Altman summed up the moment with a simple emoticon: the frowny face.

Typically, “quitting while ahead” is advantageous in debating, gambling, and even trading. But it’s not recommended in business. OpenAI, however, had no choice. Demand for ChatGPT had exceeded the company’s GPU capacity.

One of the most advanced AI companies in the world had run out of “compute.”

Other AI startups ran into the same issue: GPUs were effectively sold out. The AI models were ready, and consumer demand was there, but the hardware to run them at scale wasn’t. GPU supply chains were still running at pre-AI demand levels.

It became the first great bottleneck of the AI era.

There weren’t enough chips, networking components, or infrastructure to power the AI explosion. In effect, the entire industry hit a wall.

Two companies sat at the center of this compute bottleneck…

And both of these AI infrastructure providers went on to capture enormous gains early in the AI boom.

Today, let’s examine both of these companies – and how they made early investors millionaires.

Then, I’ll reveal how it’s not too late for investors to jump in on AI’s next wave of millionaire-maker bottlenecks.

We’ll get started with Nvidia Corp. (NVDA).

It sounds hard to believe now, but for decades, Nvidia was a terrible stock…

Turning a Compute Shortage Into a Gold Mine

Jensen Huang founded Nvidia in the early 1990s to supply graphics processors to the videogame industry. But gaming GPUs were a cyclical business. Investors who bought near the peaks often saw losses of 70% or more during downturns.

Ten thousand dollars invested in Nvidia in October 2018, for example, was worth just $4,400 less than three months later.

While Nvidia gradually expanded into automotive and mobile chips, it wasn’t until generative AI arrived that the companyturned into a great stock.

AI models require enormous computing power to train and operate. And once ChatGPT burst onto the scene, the companies racing to build AI systems suddenly needed vast quantities of high-performance GPUs.

The problem was that almost no one could supply them.

Nvidia’s chips — particularly the H100 — quickly became the gold standard for AI training. As demand surged, the company went from selling $2,000 graphics cards to gamers to selling $30,000 GPUs to data-center operators.

At the peak of the shortage in 2023, some H100 cards were reportedly reselling for more than $40,000 on eBay.

And as the AI boom accelerated, the company’s data center division exploded. Within a year, it became Nvidia’s largest business segment, with AI chips driving the vast majority of the growth.

In effect, Nvidia turned the compute bottleneck into a business moat.

Anyone building advanced AI models needed Nvidia’s GPUs.

Today, more than two years later, nearly every major AI company still depends on them.

Investors who recognized the compute bottleneck early were richly rewarded. Going back to the launch of ChatGPT as the start of the AI compute constraint, Nvidia shares have surged nearly 1,000%.

That’s the power of getting positioned before a bottleneck breaks open.

But GPUs were only part of the story…

The Networking Bottleneck Few Saw Coming

Training and operating AI models requires far more than powerful GPUs.

It also requires thousands of those GPUs to communicate with each other at extraordinary speeds inside massive data centers.

If data can’t move quickly enough between chips, the GPUs sit idle waiting for information. And idle GPUs are enormously expensive.

This created another bottleneck: data center networking.

That’s where Broadcom Inc. (AVGO) comes in.

Broadcom specializes in the networking semiconductors that allow enormous clusters of GPUs to function as a single system. Its Tomahawk and Jericho chips help move data through the world’s fastest data centers while preventing congestion.

As hyperscalers raced to build ever larger AI data centers, demand for these networking chips surged.

Broadcom also began designing custom AI accelerator chips for companies such as Alphabet Inc. (GOOG) and Meta Platforms Inc. (META) — processors optimized for specific AI workloads.

Together, these businesses positioned Broadcom directly in the path of the AI infrastructure boom.

Nvidia solved the compute bottleneck.

Broadcom helped connect that compute.

Since the launch of ChatGPT, Broadcom shares have soared roughly 600%.

And just like Nvidia, the company’s gains were driven by investors recognizing a bottleneck before the rest of Wall Street fully understood it.

But the compute and networking constraints that fueled those gains are beginning to ease.

The next phase of the AI boom will revolve around entirely different bottlenecks…

AI’s Next Bottlenecks Could Be Even Bigger

At the start of the AI boom, the biggest gains didn’t come from the companies building AI applications. They came from the companies supplying the infrastructure needed to run them.

Investors who recognized that early understood something critical: AI demand wasn’t the issue. Compute supply was.

Investors who identified that compute bottleneck early — and positioned before Wall Street fully priced it in — captured historic upside. But to harvest those gains, you have to leave the party before it ends.

For example, I recommended shares of Advanced Micro Devices Inc. (AMD) to my Fry’s Investment Report subscribers in March 2025 as a play on the compute bottleneck. Just about six months later, in October, we booked 107% gains.

We harvested those gains quickly because I saw the compute party was ending. That bottleneck was no longer driving AMD’s share-price growth.

Since the end of October, AMD has dropped more than 20%. Over that same stretch, Nvidia has fallen about 15% and Broadcom is down roughly 10%.

While the AI compute bottleneck hasn’t disappeared, its greatest gains are likely behind us.

But AI development didn’t stop.

That means more bottlenecks are already emerging.

Just like the GPU shortage that forced Sam Altman to pause new ChatGPT subscriptions in 2023, these moments remind us that technological revolutions often run into real-world limits.

In fact, I believe the market could begin recognizing these constraints as soon as April 24, when several of the largest AI hyperscalers report earnings. If those companies begin acknowledging the supply limits forming around metals, electricity, and memory, investors may suddenly realize the AI boom is running into physical limits.

That’s why I’ll be discussing this idea in more detail during FutureProof 2026on Wednesday, March 18 at 1 p.m. ET. During that free broadcast, I’ll explain why these infrastructure constraints could soon trigger a major shift in the AI trade — and why shortages in metals, electricity, and memory are becoming the next major bottlenecks.

You can reserve your spot by going here.

I’ll also share the names and tickers of 15 companies already beginning to benefit from these emerging bottlenecks. If history is any guide, the next Nvidia-style winner may come from the companies solving AI’s newest constraints.

Sign up here.

Regards,

Eric Fry

Editor, The Speculator

The post AI’s Next Bottlenecks Could Mint New Millionaires appeared first on InvestorPlace.

The massive buildout of AI infrastructure isn’t a single race – it’s a rolling gold rush driven by a sequence of AI infrastructure bottlenecks.

Each time hyperscalers run into a constraint – GPUs, servers, cooling, power, memory – the market floods capital toward the companies that solve it. Those companies become the next wave of winners.

The winning strategy isn’t buying what just worked. It’s identifying which constraint hyperscalers will throw hundreds of billions of dollars at next.

The good news is that the pattern is remarkably consistent. The better news? We can see the next bottleneck forming right now.

It sits deep inside the data center itself: the network plumbing that moves data between GPUs.

And if you catch this cycle early, the upside can be enormous.

To see how the AI infrastructure bottleneck cycle works, look at the previous phases of the AI buildout.

The Previous AI Infrastructure Bottlenecks

We’ve already seen how this cycle plays out when a new AI bottleneck emerges.

Each of these waves followed the same arc: obscurity, recognition, euphoria, rotation. In every case, hyperscalers had identified a specific constraint that prevented them from deploying capital productively – and the market rewarded whoever solved it.

That pattern is repeating again right now. And the next bottleneck is already visible.

The Next AI Bottleneck: Data Center Networking

As AI clusters grow from thousands of GPUs to hundreds of thousands of GPUs – and as the architectural ambition shifts from training giant monolithic models to running distributed inference across sprawling, always-on infrastructure – the internal plumbing of the data center has become the binding constraint.

We are talking about interconnects: the cables, transceivers, switches, and signal-processing chips that move data between GPUs, servers, racks, and buildings. 

GPUs are only as powerful as the data pipeline feeding them. If information can’t move fast enough between chips, racks, and clusters, even the most advanced processors spend time sitting idle. In a world where a single GPU can cost tens of thousands of dollars, idle time becomes extremely expensive.

The hyperscalers understand this. Broadcom (AVGO) CEO Hock Tan made it explicit in the company’s most recent earnings call, distinguishing between scale-up networking (connecting GPUs tightly within a cluster) and scale-out networking (connecting clusters to each other across a data center). This is not semantic hairsplitting. It is the architectural distinction that determines who wins the next leg of the AI infrastructure trade.

Copper vs. Optical Interconnects

The central tension in the interconnect space is a technology debate: copper or optical fiber?

Direct Attach Copper (DAC) cables are the incumbent for short-distance, in-rack connections. They are passive – no active electronics, no lasers, no photodetectors. They are cheap, low-latency, and power-efficient. However, they pose a glaring issue: copper signal integrity degrades rapidly at high data rates over distance. At today’s cutting-edge 800G speeds, usable DAC cable lengths have shrunk to roughly three meters. As data rates increase toward 1.6T, copper’s range gets even shorter.

Optical transceivers, on the other hand, convert electrical signals to light pulses, transmit them over fiber, and convert them back. Distance is no longer a constraint. But the downsides are still real – active components consume five to 15 watts per port, add latency at the conversion step, and cost materially more than copper. But for connecting clusters across a data center, there are very few practical alternatives today.

Active Electrical Cables (AEC) – copper cables with embedded signal-processing chips – represent the emerging middle ground, extending copper’s usable range to seven to 10 meters while consuming roughly 25- to 50% less power than optical alternatives. They are copper’s last stand before the physics wall, and they are genuinely good technology for the near term.

Broadcom CEO Hock Tan chimed in on this debate last week during the company’s quarterly conference call. His argument was this: push copper as deep into the architecture as physics allows, because on every dimension that matters in scale-up – latency, power, cost – copper wins. 

The takeaway from his comments is that copper dominates most scale-up connections today, while optics handles the longer-distance links. He may be right. But it is important to note that Broadcom’s entire custom AI silicon architecture happens to be optimized for copper-dominant topologies. So, it’s not surprising that a company optimized for copper-heavy architectures sees advantages in copper.

The more rigorous version of the argument is that the copper vs. optics debate is not binary. It is temporal. 

For investors, that means this is a sequence, not a single trade.

Copper wins in scale-up today. Optics wins in scale-out today. Once co-packaged optics (CPO) technology matures – which integrates photonics directly onto the chip package and eliminates the power and latency penalties of optical conversion – optics will likely win both eventually. 

The industry consensus puts CPO at commercial scale somewhere in the 2027-29 window. Nvidia just made a $4 billion bet – split between Lumentum (LITE) and Coherent (COHR) – that this timeline is real and that it intends to control the supply chain when it arrives.

In other words… copper wins the battle today, as Tan suggested… but optics will likely win the war in the long run. And that means the intelligent trade right now is to own both, then selectively rotate into optics over copper. 

The Near-Term Winners: Copper Interconnect Stocks

These are the names that benefit from Hock Tan’s world – the copper-dominant scale-up architecture that defines today’s hyperscaler buildout.

• Credo Technology (CRDO) – the closest thing to a pure-play copper interconnect stock in the public market. Credo makes AEC silicon, and its technology claims 75% less rack space than DAC cables and significantly lower power consumption than comparable optical links. It has had explosive revenue growth – a 67% quarter-over-quarter guidance raise in late 2024 – and is increasingly used inside hyperscaler AI clusters – including deployments tied to Amazon, Microsoft, and xAI – where its active electrical cables connect high-density GPU servers inside large training racks. High beta, high conviction, appropriate for investors who want maximum leverage to the near-term copper buildout.
• Marvell Technology (MRVL) – a more diversified play but deeply strategic. Marvell is the only company that ships ACC, AEC, and AOC silicon across the full connectivity spectrum. It benefits regardless of where the copper-to-optics boundary ultimately settles, which makes it a useful hedge. It is also a major custom AI ASIC supplier – its silicon powers Google TPUs and Amazon Trainium – giving it multiple vectors into the AI infrastructure trade beyond interconnects alone.
• Broadcom – Hock Tan’s company is the dominant Ethernet switching ASIC supplier for AI clusters. When he says copper is optimal in scale-up, he is describing the topology that his own switching chips sit at the center of. Broadcom is not a pure interconnect play – it is the largest custom AI silicon company in the world. But the interconnect thesis is directly supportive of its networking franchise.
• Amphenol (APH) – the physical connector and cable layer. Less exciting than the chip plays, but a reliable compounder that touches every data center buildout regardless of which medium wins the technology debate. If you are building interconnect exposure and want something that will not keep you up at night, Amphenol is the institutional-quality version of this trade.

The Long-Term Winners: Optical Networking

These are the names that own the future – the scale-out work that is happening right now, plus the CPO transition that arrives over the next three to five years.

• Lumentum – one of the first companies shipping 200G-per-lane EML lasers at volume, which happen to be the critical component inside next-generation 1.6T optical transceivers. In early March 2026, Nvidia invested $2 billion in Lumentum with multi-year procurement commitments and capacity rights. Jensen Huang called Lumentum his partner for “the next generation of gigawatt-scale AI factories.” That is a supply chain lockup. The stock was up roughly 250% over the prior year; and the valuation, while elevated, reflects a genuine structural position in a constrained market.
• Coherent – Lumentum’s primary competitor and, by some measures, the bigger optical business. Coherent received the other $2 billion from Nvidia in the same announcement. The investment thesis is slightly different: Coherent is the industrial-scale, multi-site manufacturing powerhouse with a broader product portfolio. It had been undervalued for most of 2025 due to investor perception of it as a legacy company – a perception that had grown increasingly disconnected from reality as its data center optics revenue scaled. For investors who want a slightly more conservative entry into the optics thematic, Coherent’s risk-adjusted profile is compelling.
• Fabrinet (FN) – the contract manufacturer that assembles and tests optical transceivers for Lumentum, Coherent, and others. Think of Fabrinet as the contract manufacturer behind much of the optical transceiver industry – assembling and testing the components designed by companies like Lumentum and Coherent. It is breaking ground on a new facility representing a 50% capacity expansion. Less upside than the component makers, but more durable – it benefits regardless of which optical supplier wins the technology race.
• Applied Optoelectronics (AAOI) – the speculative small-cap option. High operating leverage to the AI optical buildout, meaningful volatility, and a stock that has historically moved sharply in both directions on any demand signal. Not for everyone – but for investors with risk tolerance who want maximum torque to the optics cycle, AAOI offers the highest leverage in the group.

The Crossover Play

• Nvidia – obviously, NVDA already won the compute wave. But it’s also quietly positioning itself to win the optical wave, too. Its $4 billion combined investment in Lumentum and Coherent, CPO switch announcements at GTC 2025, and aggressive pre-allocation of EML laser supply are the actions of a company that does not intend to be dependent on an optical supply chain it does not control. Nvidia is not just a beneficiary of the interconnect buildout. It is trying to own it.

The Two-Phase AI Networking Investment Cycle

The copper-versus-optics debate becomes much clearer when you introduce one critical variable: time.

This is a two-phase trade.

Phase 1: Now through approximately 2027. The copper plays have near-term earnings momentum with less valuation risk. The architecture Hock Tan described – copper-dominant scale-up, optical scale-out – is the one being deployed right now in every major hyperscaler buildout. Credo and Marvell have the strongest revenue tailwinds in this phase. APH, too. Buy them. Hold them. Do not overthink it.

Phase 2: 2027 through 2030 and beyond. CPO commercialization, increasing cluster scale, and the workload mix shifting toward inference will erode copper’s scale-up advantage. Optical interconnect revenue is projected to grow from roughly $16 billion in 2024 to somewhere between $34 billion and $41 billion by 2030. Silicon photonics alone could reach $12- to $16 billion by 2032. The names with the longest runways in this phase are Lumentum, Coherent, and Fabrinet – the companies Nvidia has already decided are critical infrastructure.

The transition name that threads both phases without needing you to call the timing precisely is Marvell. It sells into the copper world today and has AOC silicon for the optical transition. It also has a custom ASIC business that is structurally tied to AI compute spending regardless of which interconnect medium wins. If you only want one name in the interconnect space and you have no tolerance for timing risk, Marvell is the answer.

The Bottom Line: The Next Phase of the AI Infrastructure Boom

The AI bull market has never been about one trade. It has been about a chain of trades – each one funding the next, each one solving a specific engineering constraint that was preventing the hyperscalers from deploying their next hundred billion dollars. 

Compute. Servers. Cooling. Energy. Memory. And now, interconnects.

The pattern is unmistakable. The hyperscalers have identified the bottleneck. And they are deploying enormous capital to solve it. 

The supply chain is constrained. The technology debate – copper versus optics – has a near-term winner and a long-term winner, and we know who they both are.

Get positioned before the rest of the market figures out that the plumbing inside the data center is about to have its Nvidia moment…

Because history shows you do not want to wait for the consensus.

The real lesson of the AI boom is simple: the biggest gains go to investors who position themselves before the market fully understands where the next phase is headed.

That principle applies not only to infrastructure – but to the companies building the AI itself.

One of the most important players in this revolution, OpenAI, is widely expected to pursue a public listing in the coming years – potentially one of the largest tech IPOs ever.

But investors who wait until the day the stock begins trading may already be late.

I recently recorded a briefing explaining a little-known way investors may be able to position themselves before the IPO headlines arrive.

Watch it right here.

The post The Next AI Gold Rush Is Inside the Data Center appeared first on InvestorPlace.

Yesterday, JPMorgan Chase did something subtle – but it’s the kind of move that should make investors sit up a little straighter.

The nation’s largest bank quietly began marking down the value of certain loans tied to private-credit portfolios, many of them loans to software companies.

It didn’t receive much attention, overshadowed by the Iran war and oil prices – but when a financial giant like JPMorgan starts adjusting the value of collateral behind a booming lending market, it’s worth asking why.

Here’s CNBC with more details:

The bank is potentially among the first major lenders to pull in leverage to the private credit industry, in a move that mirrors steps taken during Covid, said a person with knowledge of the matter…

The bank’s giant Wall Street trading division has reduced the value of loans — most of which were made to software firms.

Now, on its own, this adjustment might not seem like a major event. But it comes at a moment when one of the fastest-growing areas of global finance – private credit – is becoming increasingly intertwined with another of the market’s most explosive trends…

AI.

Investors need to trade carefully…

You see, a growing share of that private credit is now funding companies racing to build AI data centers and cloud infrastructure – a capital-intensive business where profits are far less certain than the demand for the raw materials powering it.

And this disconnect between spending and profits is where risks – and opportunities – are beginning to emerge.

To unpack this, let’s start with the debt piece…

Private credit has ballooned into a multi-trillion-dollar industry over the past decade

As regulators tightened bank lending after the 2008 financial crisis, private lenders stepped in to fill the gap, offering loans to companies that traditional banks might hesitate to finance.

For borrowers, the appeal is flexibility. For lenders, the appeal is yield.

But the entire system rests on a simple assumption: borrowers will continue generating enough cash flow to service their debt.

Many of those borrowers operate in technology and software – industries that are currently pouring enormous sums of money into AI infrastructure.

The bet is that those enormous sums of money will eventually produce massive new revenue streams. But that’s far from certain.

Which brings us to another headline from yesterday involving one of the companies right at the center of the AI boom…

Oracle’s surge – and the gamble beneath it

Yesterday, Oracle shares jumped as much as 14% after the company reported strong quarterly results and reassured investors about its ability to finance its aggressive expansion of AI infrastructure.

During the company’s earnings call, Oracle executives emphasized that the firm does not plan to raise additional debt in 2026 beyond what it has already announced, and that the overall economics of its buildout still works.

Here’s Oracle CEO Clayton Magouyrk:

We continue to get better and better at running these data centers, delivering them more cheaply, optimizing the amount of cost for networking and hardware spend, as well as power.

This message was clearly designed to calm investors’ nerves about Oracle’s massive spending on AI data centers – and it worked.

Wall Street interpreted Oracle’s earnings results and the comments about funding data centers as a bullish sign – “demand is strong and the spending race is still manageable!”

But still, investors piling into yesterday’s ORCL rally are making a huge gamble – one that our macro expert Eric Fry decided wasn’t worth it when he exited Oracle last fall, even after leading his Investment Report subscribers to a 27% gain.

To be fair, Oracle isn’t the only company making this risk bet. Here’s Eric explaining this broader gamble behind the AI boom:

Everyone seems to believe that AI is a miracle, but no one seems to know what this miracle means. All that we know for certain is that AI isn’t free.

The price tag for the technologies and infrastructure that enable AI will run into the trillions of dollars, but the payoff for this investment remains as inscrutable as a Delphic oracle…

Imagine going into a grocery store where no item showed a price tag, and you didn’t discover the total cost until you passed through the checkout line.

AI is that grocery store.

This uncertainty isn’t just theoretical

When you start digging into the economics behind the AI infrastructure boom, the numbers can get uncomfortable very quickly.

Eric’s lead analyst in Fry’s Investment Report, Tom Yeung, recently walked through an illustration using Oracle, which was part of the reason why Eric sold.

Last September, Oracle signed a massive agreement to provide cloud computing capacity to OpenAI. Here’s Tom breaking down the numbers:

Oracle signed a $300 billion cloud deal to provide 4.5 gigawatts of cloud computing power to OpenAI between 2027 and 2032.

We know that each data center gigawatt costs roughly $50 billion to build – $35 billion for Nvidia chips, and another $15 billion for everything else…

That means Oracle will spend around $225 billion through 2027 ($50 billion × 4.5) to build these data centers to make $300 billion in revenue.

Now, if everything goes perfectly, the project could generate enormous profits. But the margin for error is thin.

If a major customer delays spending… if pricing pressure emerges… or if AI demand doesn’t materialize as expected, those economics could change very quickly.

And remember, Oracle doesn’t have some massive technological edge in its AI, which puts even more weight on the economics of these deals.

Back to Tom:

At its core, AI computing is a service that’s mostly indistinguishable between providers. They all use the same Nvidia Corp. (NVDA) chips running on the same platform.

So, choosing between providers usually comes down to price.

That’s not an ideal setup for companies spending hundreds of billions of dollars to build AI infrastructure while betting on future revenue to justify the investment.

Circling back to private lending, we’re already seeing hints of stress in the financing ecosystem supporting this buildout.

For example, private credit giant Blue Owl Capital – a major lender to technology and software companies – recently faced a surge in redemption requests from investors in one of its funds, forcing the firm to restrict withdrawals and sell roughly $1.4 billion in loans to raise liquidity.

Bad AI loans were not the cause specifically. But it highlights something important: a huge share of private-credit lending today is tied to software companies whose business models may themselves be disrupted by AI.

And that’s exactly the kind of scenario JPMorgan’s quiet loan markdown may be hinting at.

So, where should investors look instead?

Where Eric sees the smarter opportunity

Eric believes the smarter move is to focus on the parts of the economy that will benefit from AI’s expansion, regardless of which software companies ultimately win.

Increasingly, those parts are the industry’s bottlenecks – the critical inputs the entire system depends on.

We’ve already seen how powerful those opportunities can be. After all, when an industry hits a bottleneck, the companies that solve it often capture enormous gains.

To illustrate, let’s begin with Eric describing one of the earliest bottlenecks of the AI era:

In November 2023 – just a year after ChatGPT’s debut – OpenAI CEO Sam Altman made a surprising decision. He suspended signups for ChatGPT’s paid subscriptions, cutting off new users from OpenAI’s advanced models.

Demand for ChatGPT had exceeded the company’s GPU capacity.

One of the most advanced AI companies in the world had run out of ‘compute.’

There weren’t enough chips, networking components, or infrastructure to power the AI explosion. In effect, the entire industry hit a wall.

That compute bottleneck turned out to be incredibly lucrative for the companies positioned to solve it.

Nvidia (NVDA) and Broadcom (AVGO) – two firms sitting directly in the path of that infrastructure shortage – delivered enormous gains for early investors as the AI boom accelerated.

Below, you can see AVGO and NVDA soaring 316% and 355% respectively since November 2023:

But as Eric explains, the compute bottleneck that fueled those early gains is now beginning to ease…which means the next phase of the AI boom will likely revolve around entirely new constraints.

Where the next bottlenecks – and opportunities – are forming

According to Eric, the next wave of AI opportunities is coming from the industries that supply the physical inputs the AI economy depends on.

Take copper, for example.

Every data center, circuit board, transformer, cable, and chip requires it. And the scale of future demand is staggering.

As Eric notes:

To maintain current growth rates, we would have to mine the same amount of copper in the next 18 years as humanity mined during the previous 10,000 years combined.

That’s the kind of physical constraint that can reshape entire industries.

But copper is only the beginning…

AI data centers require enormous amounts of electricity to operate. They depend on specialized memory chips to run AI models. And they rely on complex supply chains of metals, cooling systems, networking equipment, and power infrastructure.

In other words, while software may capture the headlines, the real-world infrastructure behind AI may ultimately determine how fast – and how profitably – the entire industry grows.

That’s why Eric is urging investors to shift their attention – and their investment dollars – toward the companies solving these physical bottlenecks.

He’ll be explaining exactly where those opportunities are during a special event called FutureProof 2026 next Wednesday, March 18 at 1 p.m. ET.

Here’s Eric:

During this free broadcast, I’ll explain why shortages in metals, electricity, and memory are becoming the next major bottlenecks in the AI boom – and why investors who identify these constraints early could position themselves for the next wave of gains.

I’ll bring you more details in the coming days, but you can reserve your spot for Eric’s FutureProof 2026 broadcast right here.

Wrapping up…

JPMorgan’s headline yesterday is a reminder that parts of today’s financial system may be taking on more risk than investors realize – especially as trillions of dollars flow into AI infrastructure.

Oracle’s rally shows the excitement is still alive. But as Eric and Tom point out, the real question isn’t whether AI will change the world – but whether every company spending billions will earn an attractive return.

So, is there a better bet?

If history is any guide, yes – own the companies supplying the tools, materials, and infrastructure that the entire system depends on.

More on how Eric is doing this over the next few days…

Have a good evening,

Jeff Remsburg

The post JPMorgan’s Quiet Warning About AI appeared first on InvestorPlace.

But this time, there’s a surprise.

The number is much higher than you expected.

Great, you think. Just what I needed.

For many Americans, electricity is already one of the largest utility expenses in the monthly household budget.

And lately, those bills have been going up in households all across the country.

The average American household now spends about $140 per month on electricity, and rising demand for power is putting additional strain on the grid.

In fact, the issue has become serious enough that officials recently met at the White House to discuss the growing strain.

That’s a problem at a time when policymakers are still trying to bring inflation down.

Now, inflation appears to be moving in the right direction. This week’s Consumer Price Index (CPI) report showed prices rose 0.3% in February and 2.4% year-over-year. Core CPI, which excludes food and energy, rose 0.2% for the month and 2.5% over the past year.

But when you dig into the details, there is one major red flag: electricity costs.  

Prices were 4.8% higher in February than a year ago, and natural gas prices climbed 10.9% over the same period. Gasoline prices fell 5.6% year-over-year in February, but they’ve jumped about 60 cents per gallon on average in just the past month.

And this is before the Iran conflict drove oil prices higher.

So, what’s behind the rising electricity costs this year?

Artificial intelligence.

In today’s ÃÛÌÒ´«Ã½ 360, I’ll explain how AI is consuming enormous amounts of power, why demand will continue growing, why tech giants are investing hundreds of billions of dollars to support it… and where the biggest opportunities for investors may lie.

The Race to Build AI’s Backbone

The world’s largest technology companies are now racing to build the infrastructure needed to power artificial intelligence.

And they’re spending staggering amounts of money to do it.

In 2025 alone, Microsoft Corporation (MSFT), Meta Platforms, Inc. (META), Amazon.com, Inc. (AMZN) and Alphabet Inc. (GOOGL) collectively spent roughly $337 billion on AI infrastructure.

And their capital spending plans suggest that number could climb to $600 billion in 2026.

That’s more than the entire annual economic output of countries like Sweden or Poland.

But here’s what many investors don’t realize.

The biggest challenge in building these massive AI systems isn’t just the chips.

The bottleneck isn’t software. It’s hardware.

You see, AI doesn’t run on code alone.

It runs on servers that can handle extreme heat, networking systems designed to connect hundreds of thousands of processors and cooling assemblies engineered for reliability.

And it needs power infrastructure capable of delivering electricity to facilities that consume as much energy as a small city.

When you’re operating systems at that scale, everything has to work perfectly.

Because when hundreds of thousands of GPUs are connected together, every component has to work flawlessly.

A single point of failure can shut down an entire system. And when you’re running facilities this large, even a short disruption can cost millions of dollars.

This means tech giants are relying on companies that design and build the infrastructure that keeps these facilities running.

That’s where the real opportunity is hiding.

The “Picks and Shovels” of the AI Boom

History shows that when an industry goes through a massive buildout like this, the biggest fortunes aren’t always made by the companies everyone is watching.

During the California Gold Rush, thousands of people rushed west, hoping to strike it rich.

Many spent years searching for gold, and only a handful actually found it.

Some of the biggest fortunes of that era were made by businesses that supplied the tools miners needed, which were picks, shovels and equipment.

A similar dynamic is unfolding in AI today.

As tech companies rush to build larger and more powerful AI systems, they need enormous amounts of infrastructure to make it all work.

That means the companies building that infrastructure could end up among the biggest winners in this shift.

And that’s exactly where I’ve been focusing my latest research.

While many investors are focused on chatbots, software and AI applications, some of the biggest opportunities may come from the companies supplying the technology that keeps these systems running.

Because the next phase of the AI boom may not be defined by software breakthroughs.

It may be defined by the infrastructure that powers them.

And that brings us back to your utility bill.

The AI boom is driving an enormous surge in demand for electricity – and the systems needed to generate, deliver and manage that power. So, don’t expect your bill to go down anytime soon.

Now, I recently put together a special presentation to further explain what’s driving this shift – and the companies that could benefit as tech giants pour hundreds of billions of dollars into building the systems behind AI.

If you want to better understand why the next phase of the AI boom needs as much electricity as it does – and the companies helping to make it possible – I encourage you to watch the full presentation here now.

Sincerely,

Louis Navellier

Editor, ÃÛÌÒ´«Ã½ 360

The post Why AI Could Drive Inflation Higher appeared first on InvestorPlace.

He stopped taking new customers. 

New signups for ChatGPT’s paid subscriptions were suddenly suspended. Anyone hoping to access OpenAI’s most advanced models was simply turned away. 

This wasn’t because demand had collapsed. 

It was because demand had exploded. In its first year, ChatGPT reached 100 million weekly active users. And after its first developers conference on November 6, 2023 – where the company unveiled ChatGPT Plus – the number of wannabe subscribers surged rapidly.  

Just a week later, Altman literally had to start turning away folks with credit cards in hand. 

Altman summed up the moment with a simple emoticon: the frowny face.  

we are pausing new ChatGPT Plus sign-ups for a bit 🙁

the surge in usage post devday has exceeded our capacity and we want to make sure everyone has a great experience.

you can still sign-up to be notified within the app when subs reopen.

Typically, “quitting while ahead” is advantageous in debating, gambling, and even trading. But it’s not recommended in business. OpenAI, however, had no choice. Demand for ChatGPT had exceeded the company’s GPU capacity. 

One of the most advanced AI companies in the world had run out of “compute.” 

Other AI startups ran into the same issue: GPUs were effectively sold out. The AI models were ready, and consumer demand was there, but the hardware to run them at scale wasn’t. GPU supply chains were still running at pre-AI demand levels. 

It became the first great bottleneck of the AI era. 

There weren’t enough chips, networking components, or infrastructure to power the AI explosion. In effect, the entire industry hit a wall.  

Two companies sat at the center of this compute bottleneck… 

And both of these AI infrastructure providers went on to capture enormous gains early in the AI boom. 

Today, let’s examine both of these companies – and how they made early investors millionaires. 

Then, I’ll reveal how it’s not too late for investors to jump in on AI’s next wave of millionaire-maker bottlenecks. 

We’ll get started with Nvidia Corp. (NVDA). 

It sounds hard to believe now, but for decades, Nvidia was a terrible stock… 

Turning a Compute Shortage Into a Gold Mine 

Jensen Huang founded Nvidia in the early 1990s to supply graphics processors to the videogame industry. But gaming GPUs were a cyclical business. Investors who bought near the peaks often saw losses of 70% or more during downturns.  

Ten thousand dollars invested in Nvidia in October 2018, for example, was worth just $4,400 less than three months later. 

While Nvidia gradually expanded into automotive and mobile chips, it wasn’t until generative AI arrived that the companyturned into a great stock. 

AI models require enormous computing power to train and operate. And once ChatGPT burst onto the scene, the companies racing to build AI systems suddenly needed vast quantities of high-performance GPUs. 

The problem was that almost no one could supply them. 

Nvidia’s chips — particularly the H100 — quickly became the gold standard for AI training. As demand surged, the company went from selling $2,000 graphics cards to gamers to selling $30,000 GPUs to data-center operators. 

At the peak of the shortage in 2023, some H100 cards were reportedly reselling for more than $40,000 on eBay. 

And as the AI boom accelerated, the company’s data center division exploded. Within a year, it became Nvidia’s largest business segment, with AI chips driving the vast majority of the growth. 

In effect, Nvidia turned the compute bottleneck into a business moat. 

Anyone building advanced AI models needed Nvidia’s GPUs. 

Today, more than two years later, nearly every major AI company still depends on them. 

Investors who recognized the compute bottleneck early were richly rewarded. Going back to the launch of ChatGPT as the start of the AI compute constraint, Nvidia shares have surged nearly 1,000%. 

That’s the power of getting positioned before a bottleneck breaks open. 

But GPUs were only part of the story… 

The Networking Bottleneck Few Saw Coming 

Training and operating AI models requires far more than powerful GPUs. 

It also requires thousands of those GPUs to communicate with each other at extraordinary speeds inside massive data centers. 

If data can’t move quickly enough between chips, the GPUs sit idle waiting for information. And idle GPUs are enormously expensive. 

This created another bottleneck: data center networking. 

That’s where Broadcom Inc. (AVGO) comes in. 

Broadcom specializes in the networking semiconductors that allow enormous clusters of GPUs to function as a single system. Its Tomahawk and Jericho chips help move data through the world’s fastest data centers while preventing congestion. 

As hyperscalers raced to build ever larger AI data centers, demand for these networking chips surged. 

Broadcom also began designing custom AI accelerator chips for companies such as Alphabet Inc. (GOOG) and Meta Platforms Inc. (META) — processors optimized for specific AI workloads. 

Together, these businesses positioned Broadcom directly in the path of the AI infrastructure boom. 

Nvidia solved the compute bottleneck. Broadcom helped connect that compute. 

Since the launch of ChatGPT, Broadcom shares have soared roughly 600%. 

And just like Nvidia, the company’s gains were driven by investors recognizing a bottleneck before the rest of Wall Street fully understood it. 

But the compute and networking constraints that fueled those gains are beginning to ease. 

The next phase of the AI boom will revolve around entirely different bottlenecks… 

AI’s Next Bottlenecks Could Be Even Bigger 

At the start of the AI boom, the biggest gains didn’t come from the companies building AI applications. They came from the companies supplying the infrastructure needed to run them. 

Investors who recognized that early understood something critical: AI demand wasn’t the issue. Compute supply was. 

Investors who identified that compute bottleneck early — and positioned before Wall Street fully priced it in — captured historic upside. But to harvest those gains, you have to leave the party before it ends. 

For example, I recommended shares of Advanced Micro Devices Inc. (AMD) to my Fry’s Investment Report subscribers in March 2025 as a play on the compute bottleneck. Just about six months later, in October, we booked 107% gains.  

We harvested those gains quickly because I saw the compute party was ending. That bottleneck was no longer driving AMD’s share-price growth. 

Since the end of October, AMD has dropped more than 20%. Over that same stretch, Nvidia has fallen about 15% and Broadcom is down roughly 10%. 

While the AI compute bottleneck hasn’t disappeared, its greatest gains are likely behind us. 

But AI development didn’t stop. 

That means more bottlenecks are already emerging. 

Just like the GPU shortage that forced Sam Altman to pause new ChatGPT subscriptions in 2023, these moments remind us that technological revolutions often run into real-world limits. 

In fact, I believe the market could begin recognizing these constraints as soon as April 24, when several of the largest AI hyperscalers report earnings. If those companies begin acknowledging the supply limits forming around metals, electricity, and memory, investors may suddenly realize the AI boom is running into physical limits. 

That’s why I’ll be discussing this idea in more detail during FutureProof 2026 on Wednesday, March 18 at 1 p.m. ET. During that free broadcast, I’ll explain why these infrastructure constraints could soon trigger a major shift in the AI trade — and why shortages in metals, electricity, and memory are becoming the next major bottlenecks. 

You can reserve your spot by going here. 

I’ll also share the names and tickers of 15 companies already beginning to benefit from these emerging bottlenecks. If history is any guide, the next Nvidia-style winner may come from the companies solving AI’s newest constraints. 

Sign up here.

Regards,  

Eric Fry 

Editor, Smart Money

The post The First AI Bottleneck Made Millionaires. The Next One Is Forming Now. appeared first on InvestorPlace.

The AI system most closely linked to U.S. operational support was Claude. Reporting indicates Anthropic‘s model was used through the Pentagon’s Maven Smart System, aided by Palantir (PLTR) in the broader defense-AI stack, to help process imagery, communications, and other intelligence inputs at machine speed. The result was a compressed kill chain: targets were analyzed, prioritized, and acted on faster than traditional human-only workflows could manage. 

Five days later, on March 4, the same country staged a very different kind of event. 

President Trump gathered the CEOs of Alphabet (GOOGL), Microsoft (MSFT), Meta (META), Amazon (AMZN), Oracle (ORCL), xAI, and OpenAI at the White House for a signing ceremony. They signed something called the Ratepayer Protection Pledge – a commitment, the administration said, to keep AI-driven data center expansion from raising household electricity bills by pushing hyperscalers to build, bring, or buy the power and infrastructure they need themselves. Some observers have started calling that emerging system the “shadow grid.”

The press covered both events, and not many people connected them. But they should have… 

Because Operation Epic Fury and the Ratepayer Protection Pledge are two chapters of the same story. And together, they may have just changed the investment calculus on energy, infrastructure, and national security more than most investors appreciate.

Why AI Data Centers Need Their Own Power

Start with what the conflict revealed about AI, because it changes the stakes of everything that follows.

The U.S. military used Anthropic’s Claude, through the Maven Smart System, to support intelligence analysis, target identification, and operational simulations during the strikes. In practice, that meant ingesting intelligence inputs, ranking targets, and helping assess strike effects once operations were underway.

In other words, AI is moving beyond the role of productivity tool or chatbot. It is now being used to process battlefields and compress kill chains. In this case, it appears to have helped accelerate the chain of analysis behind one of the most consequential strikes of the decade.

Now ask the question almost every financial analyst is failing to ask: what does that mean for the AI infrastructure build-out?

It means the shadow grid isn’t just a commercial infrastructure story anymore. It’s a national security story. The compute capacity that enables AI is now powering the operational backbone of U.S. military dominance. And the energy that powers that compute is, as of this week, as strategically critical as an aircraft carrier.

Meanwhile, the war is doing something else that directly accelerates the shadow grid thesis. 

A Shadow Grid In Overdrive

Iran launched retaliatory missile and drone strikes targeting U.S. embassies, military installations, and oil infrastructure – including vessels in the Strait of Hormuz – throughout the Middle East. The strait is now effectively blocked for normal commercial traffic, and oil prices have surged sharply as markets price in a major supply disruption.

Translation: the global energy system just became less reliable and more expensive precisely when America is trying to power the largest technology buildout in its history. That is a pressure cooker.

And the hyperscalers – who were already planning to build private energy infrastructure before the war – now have an argument that goes far beyond cost management. They have an argument that goes to the survival of the American technological advantage itself.

That brings us back to the public grid – the one your home is connected to. 

The Energy Demands of the AI Economy

Power demand from U.S. data centers doubled between 2018 and 2024 and could triple by 2028. There are roughly 680 data centers currently being planned in the United States, collectively requiring the energy equivalent of 186 large nuclear power plants. The public grid was not designed for this. Capacity prices in PJM Interconnection – the largest U.S. power market, spanning 13 states and D.C. – have surged to record highs, with recent auctions clearing around $329 to $333 per megawatt-day. That is a system under mounting strain.

So, what do you do if you’re Microsoft or Google and you need absolute power reliability for a campus consuming as much electricity as a small city – a campus that is now, demonstrably, part of America’s national defense infrastructure? 

You don’t wait for the utility to figure it out. You build your own.

Private natural gas plants. Long-term nuclear power purchase agreements. Small modular reactors built directly into the data center footprint. Independent transmission lines, substations, and switching infrastructure.

One grid for the AI economy. One grid for everyone else. 

This bifurcation is underway. And the Iran War just turbocharged it.

The AI Infrastructure Buildout

The shadow grid is likely to be the most capital-intensive build-out in the American economy since the interstate highway system. And like the highway system, it doesn’t just benefit the end users. It creates enormous, durable value for everyone supplying the materials, the equipment, the engineering, and the fuel.

But here’s the new layer that Operation Epic Fury adds: Washington is now an explicit partner in ensuring that AI infrastructure gets built. An AI-first military strategy is no longer just a memo or a concept paper; it now has a demonstrated operational dimension, visible in the opening phase of one of the most significant military operations of the decade. The U.S. Department of Defense has formally embraced a blueprint to make AI foundational to how U.S. armed forces fight, gather intelligence, and organize operations across all domains.

When the Pentagon’s warfighting strategy runs on the same compute infrastructure that Microsoft and Google are building, “AI infrastructure” stops being a corporate capex story and becomes a defense appropriations story. The political tailwind doesn’t just include Trump’s Ratepayer Protection Pledge. It includes the entire national security establishment recognizing, in real time, that AI is how America wins wars.

That creates a very different political environment for energy permitting, nuclear licensing, and infrastructure investment than the one that existed just two weeks ago.

The smart money figured this out before the war. 

But the shadow grid trade – now supercharged by the national security imperative – still has years of runway, and most investors are still thinking about AI as a software story. They’re wrong. Increasingly, the constraint on AI is physical – power, cooling, land, and the equipment to manage all three. 

That’s where the alpha is.

The Companies Building the AI Power Grid

GE Vernova (GEV) may be the single best-positioned large-cap in this trade – gas turbines, grid equipment, and electrification infrastructure under one ticker. Eaton (ETN), Hubbell (HUBB), and Quanta Services (PWR) capture the power infrastructure buildout. Vertiv owns the precision cooling market. These are infrastructure suppliers to a build-out that is now simultaneously supported by corporate capex, White House policy, and Pentagon warfighting strategy.

The Energy Companies Fueling AI

Vistra (VST) and Constellation Energy (CEG) are transitioning from commodity power producers into critical AI infrastructure partners. The Iran War and the Hormuz disruption just made domestic generation assets significantly more valuable relative to import-dependent alternatives. Constellation’s 20-year power purchase agreement with Microsoft is the template. More deals are coming. The repricing of these companies as strategic infrastructure is not complete.

We think nuclear is the most differentiated angle in the entire trade – and the Iran War makes it more urgent, not less. The Hormuz crisis is a direct argument for nuclear: it is the one large-scale generation technology that is completely immune to Middle Eastern oil supply disruptions. No pipelines, tankers, or exposure to any Iranian retaliation against Gulf oil infrastructure. Domestic uranium, domestic fuel cycle, domestic output. Cameco (CCJ) and Uranium Energy Corp (UEC) win regardless of which reactor design prevails. BWX Technologies (BWXT) builds the reactor components and carries defense exposure as a second thesis – a name that just became meaningfully more interesting given the demonstrated role of AI in military operations.

The Overlooked Infrastructure Behind AI Data Centers

Water infrastructure remains almost entirely absent from the AI infrastructure conversation – yet every hyperscale campus is also a water-intensive industrial site. Data centers need water for cooling, heat rejection, fire suppression, treatment, and pressure management – and the larger the campus, the more complex that plumbing and control stack becomes. Xylem (XYL), Watts Water Technologies (WTS), and Mueller Water Products (MWA) are quiet beneficiaries of every shadow grid campus that breaks ground.

And alongside the U.S.-Iran conflict, the Operational Technology (OT) cybersecurity angle just became far more urgent. Iran’s Revolutionary Guard Corps has long been associated with advanced cyber activity, including campaigns aimed at disrupting industrial and operational technology environments. When you are building a private power grid for America’s AI-driven national security infrastructure, protecting that grid from cyber retaliation is not optional. Palo Alto Networks (PANW) and Fortinet (FTNT) both have OT security exposure. This trade just went from interesting to essential.

How the Shadow Grid Threatens Traditional Utilities

Regulated utilities have been the widow-and-orphan trade for over a century. Boring. Dividend-paying. Rate-regulated. Backed by state-guaranteed returns on capital.

The shadow grid breaks that assumption for the highest-value customers in the grid’s history. And the Iran War and Strait of Hormuz disruption break it further – because they create additional pressure to accelerate private, domestic, insulated power infrastructure at the expense of the shared grid.

The stranded asset problem is real and underpriced. When a utility in Virginia or Ohio upgraded its transmission infrastructure to serve a new hyperscale data center campus, it issued bonds, capitalized that investment at a regulated rate of return, and built its next rate case around projected AI load growth. But if the hyperscaler builds its own generation and goes behind-the-meter, the utility spent billions on infrastructure for a customer who is leaving. 

That debt doesn’t disappear. It gets passed to ratepayers – aka folks like you and me.

The Defensive Move

For investors, the load growth projections baked into utility valuations in data-center-heavy service territories are increasingly fictional. Dominion Energy (D), Duke Energy (DUK), and American Electric Power (AEP) all have significant data center exposure in their service territories. The market is still pricing them as if that load is sticky.

Add the Iran-driven oil price shock – Brent crude approaching $120, natural gas markets tightening, import-dependent generation costs rising – and the cost structure assumptions for the most exposed utilities get hit from two directions at once. Load-growth assumptions weaken as hyperscalers move behind the meter. Input costs rise as the Middle East crisis tightens global energy markets.

Rotating out of utility sector ETFs – which are heavily weighted toward the most exposed names – is the prudent defensive move for any portfolio that built a utility position on the assumption that AI demand would be a tailwind rather than an exit.

The Bottom Line: The Shadow Grid Is Coming

The shadow grid was always a story about who controls the physical foundations of the next economy.

Operation Epic Fury just made it a story about who controls the physical foundations of the next war.

When the AI that helps locate and eliminate a supreme leader runs on privately built compute powered by privately built energy infrastructure, the shadow grid stops being a corporate moat story and becomes a national power story.

The same infrastructure that gives Microsoft a competitive advantage in enterprise software increasingly gives America a strategic edge over its adversaries.

Washington understands this now. The hyperscalers have known it for years – which is why they were already building before Trump held a signing ceremony – and before the bombs started falling.

The question is no longer whether the shadow grid gets built. It’s whether your portfolio is positioned to benefit from it.

One company sits closer to the center of that AI power race than almost any other: OpenAI.

The same organization that helped ignite the modern AI revolution is now widely expected to pursue a public listing – potentially the most anticipated technology IPO of the decade.

But investors who wait until the day OpenAI rings the opening bell may already be late.

That’s why I recently put together a special briefing explaining a little-known way investors may be able to position themselves before the IPO headlines arrive.

You can see the full breakdown here.

The post The Shadow Grid: Big Tech’s Quiet Takeover of America’s Power appeared first on InvestorPlace.

This morning, the latest Consumer Price Index (CPI) numbers came in as expected.

Headline inflation increased 0.3% for the month and 2.4% on the year – both numbers matched consensus forecasts.

Meanwhile, core CPI (which strips out volatile food and energy prices) edged 0.2% higher on the month and 2.5% over the last year. These numbers were also in line with estimates.

One noteworthy part of the report came from the shelter component, the CPI’s largest weighting…

For years, stubbornly high shelter prices put upward pressure on the overall inflation reading. But this morning, this component came in at 0.2% on a month-over-month basis. And within it, rent costs rose just 0.1% – the smallest monthly increase since January of 2021.

But the main headline from this morning’s report? These numbers don’t matter.

Under normal circumstances, today’s CPI figures would be exactly what investors want to see – more confirmation that inflation is gradually easing and the Federal Reserve can inch closer to cutting interest rates.

But the data reflect the economy that existed before the oil shock triggered by the Iran war.

So, while the numbers were largely good, they’re already outdated.

The biggest variable in the inflation outlook today isn’t rent, eggs, or deodorant…

It’s oil.

As you know, the Iran conflict triggered a sudden spike in crude prices, briefly sending oil soaring to roughly $115 per barrel on Sunday evening at the height of the panic.

Since then, prices have pulled back sharply, falling into the upper-$80s as I write on Wednesday at lunch.

That drop is resulting in many investors breathing a sigh of relief – the assumption being that the worst of the inflation scare is already behind us.

But while that drop from $115 to $87 grabs the headlines and is somewhat comforting, is it the right focal point for investors?

Wouldn’t the more relevant comparison be current prices to where oil traded before the conflict erupted?

Over the week before U.S. strikes on Iran – February 21–27 – the average price of West Texas Intermediate Crude (WTIC) was just over $65 a barrel.

That means today’s WTIC price is 34% higher than it was two weeks ago.

The key question today is whether oil settles back toward its earlier range or becomes entrenched at higher levels.

This morning, the International Energy Agency (IEA) agreed to release 400 million barrels of oil – its largest release ever – to smooth the disruption caused by the war in the Middle East.

From IEA Executive Director Fatih Birol:

The oil market challenges we are facing are unprecedented in scale, therefore I am very glad that IEA Member countries have responded with an emergency collective action of unprecedented size.

Will it be enough to bring WTIC prices back into the $60s?

The answer will matter far more for the inflation outlook than anything in this morning’s CPI report.

We’ll keep tracking this.

Oil isn’t the only commodity reacting to the war

Another key industrial metal quietly surged last week as supply fears rippled through global markets – aluminum.

As our global macro investing expert Eric Fry, editor of Fry’s Investment Report, recently noted, the conflict in the Persian Gulf has sent aluminum prices surging nearly 10%, pushing the metal to a three-year high.

Source: TradingEconomics

The Middle East supplies roughly 9% of the world’s aluminum, meaning any disruption to shipments can quickly ripple through global supply chains.

But volatility can create an opportunity for investors. Plus, even if tensions cool, aluminum still enjoys a powerful structural tailwind.

Here’s Eric explaining:

If the war continues to create a global aluminum shortage, mining companies could stand to benefit…

And beyond the escalating conflict, aluminum demand has increased thanks to AI’s need for infrastructure and hardware…

Every high-voltage line that feeds an AI data hub consumes 1 to 2 tons of aluminum per megawatt of delivered power. Each new stretch of long-distance transmission deepens the world’s appetite for this versatile metal.

From 104 million tons of demand in 2024 to an estimated 120 million by 2030, global aluminum consumption is set to grow relentlessly.

This lines up perfectly with a theme we’ve been highlighting in recent Digests – investing in the “physical backbone” of AI.

Even if the AI trade runs into headwinds, AI itself isn’t going away. Some software platforms and high-multiple application stocks may struggle, but the infrastructure powering AI will remain essential.

This means datacenters, advanced semiconductors, power generation, and rare earths and critical minerals/metals – like aluminum – remain mission-critical.

So, how do you invest?

Eric just highlighted Alcoa (AA), the largest U.S.-based aluminum producer. His Investment Report subscribers are up 71% in this position, but as AI demand increases, that return is likely to keep climbing.

Back to Eric:

After suffering a tariff-induced selloff earlier in the year, Alcoa’s shares have been trending higher.

I expect that uptrend to gain momentum – driven not only by firmer aluminum prices, but also by the company’s exceptional fundamentals…

In the end, the market may reward not those who build the virtual world, but those who power it. The AI Revolution will always need its dreamers, but it will depend on the miners that turn metal into its bones.

Now, while Eric just outlined the fundamental case for owning AA, traders should watch AA’s developing technical setup…

Is AA about to resume its breakout?

In the AA chart below, I overlay a stage-analysis framework.

Stage analysis is a classic trading approach popularized by legendary technician Stan Weinstein and frequently used by our hypergrowth expert Luke Lango.

Notice how AA spent much of the past year in a classic Stage-2 advance. But here in 2026, it’s transitioned into Stage 3 – a pause where buyers and sellers battle to determine the next major move.

To make sure we’re all on the same page, stage analysis simply breaks every stock’s life cycle into four phases:

• Stage 1: A bottoming period where prices move sideways
• Stage 2: A sustained advance driven by heavy buying pressure
• Stage 3: A topping pattern where momentum fades
• Stage 4: A decline as sellers take control

The biggest gains occur during Stage 2, when a stock breaks out of a base and begins trending higher for months – sometimes years.

This is exactly what Alcoa did last year. After volatile basing in 2023 and 2024, AA finally broke out in 2025, with its gains accelerating last fall.

That advance carried the stock all the way into the mid-$60s earlier this year, where it has since been consolidating in Stage 3.

Now, as I noted earlier, in this stage, buyers and sellers battle for where the stock goes next. So, traders need to watch price action and volume closely to make sure they avoid buying in as AA slips into Stage 4.

However, given Eric’s macro analysis, we believe the fundamental winds are far more likely to push AA back into Stage 2.

This leaves the technicals as the potential starting gun for the next leg higher.

Specifically, if Alcoa breaks convincingly above its recent trading range (around $66) on heavy volume – roughly two to three times normal levels – that would signal Stage-2 momentum is likely returning. And that’s a breakout to consider buying.

Stage analysis is about letting price reveal what’s happening in real time

If AA pushes higher, the chart will confirm it…

If it breaks lower, price will tell that story just as clearly…

This focus on price action sits at the core of Luke’s stage-analysis trading approach.

The challenge is that spotting these Stage-2 breakouts consistently isn’t easy. Thousands of stocks are trading at any given moment, and only a small fraction are setting up for the kind of moves traders want to capture.

That’s why Luke and his team built a system designed specifically to scan the market for the best opportunities.

Here he is explaining how it works:

Identifying true Stage 2 breakouts across thousands of stocks before they move requires serious analytical horsepower.

That’s why my team and I have built a system that quantifies the stage analysis framework into a proprietary scoring model – grading thousands of stocks in the market from 0 to 5 based on the strength of their momentum setup.

In back-testing, it flagged eight of 2025’s top-performing stocks before their big runs, including:

• Hycroft Mining Holding Corp. (HYMC)before a 1,100% move.
• Terns Pharmaceuticals Inc. (TERN) before an 865% surge.
• MP Materials Corp. (MP) months before the Pentagon deal and a partnership with Apple Inc. (AAPL) sent it to the moon.

Right now, several AI-infrastructure stocks – including companies tied to metals, power, and semiconductors – are flashing breakout signals.

If you’d like to see more about how the system works – as well as a free stock that’s currently soaring in Stage 2 – you can watch Luke’s free presentation right here.

Back to Luke:

The system doesn’t chase headlines. It looks for one thing. Stocks on the verge of entering Stage 2.

In a market driven by algorithms and geopolitical shocks, reading price structure instead of predicting headlines isn’t optional – it’s essential.

We’ll keep tracking all these stories – and the related price action – here in the Digest.

Have a good evening,

Jeff Remsburg

The post Good CPI Numbers…Are Irrelevant appeared first on InvestorPlace.

Eric wrote to his readers… 

Liberty offers an innovative suite of completion services and technologies to onshore oil and gas exploration and production companies… including next-generation all-electric fracking fleets. 

Within two years, shares of the fracking company had surged 70% – even as oil prices dropped below $80 per barrel, down from $90. 

That’s because companies like Liberty don’t rely on sky-high oil prices to make money. The Colorado-based firm earns money from completing new wells, regardless of energy prices.  

In addition, many of America’s top shale producers are now so low-cost (in part from Liberty’s technologies) that they can remain profitable even if oil falls below $50 per barrel. 

These are the types of bets we like making: one-sided “heads-I-win, tails-I-don’t-lose” wagers.  

ÃÛÌÒ´«Ã½s are once again learning the importance of one-sided bets as the war in Iran turn oil markets into a guessing game. 

On Tuesday, oil prices continued their double-digit decline after the White House said that “the war is very complete, pretty much.” The Pentagon soon painted an entirely different picture by stating, “We will not relent until the enemy is totally and decisively defeated.” Crude futures soon jumped double digits again. 

Most speculators are playing the volatility the obvious way. They’re piling into oil ETFs and large-cap energy names… watching the WTI price ticker like it’s a scoreboard and hoping for the best.  

But oil prices are unpredictable. Speculators win if prices go up… and lose equally if they go down. They might as well make money from guessing coin flips. 

That’s why I want to look at companies with far better odds. These are investments that should do well, no matter where oil prices go. 

So, to help protect your portfolios during this Middle East conflict, I’d like to highlight a Fry’s Investment Report holding that should do well, regardless of whether oil surges to $120 or falls back to Earth. 

The company is dealing with a fertilizer crisis that has barely registered on Wall Street’s radar, even as the signals are already flashing.   

Then, I’ll share where you can find two additional plays that are benefiting from high oil prices.  

Let’s take a look… 

Winning Wager Buy No. 1 

The Middle East isn’t just an oil and gas hub. It’s also a critical supplier of nitrogen-based fertilizers. Since 2020, six countries in the Persian Gulf have exported $50 billion of these crucial agricultural inputs. That means roughly 25% to 30% of global fertilizer exports pass through the Hormuz Strait. 

Put another way, the Gulf states have a bigger share of the fertilizer market than they do of the oil and gas market. 

The most direct beneficiaries have already seen the news reflected in share prices. CF Industries Holdings Inc. (CF) has surged over 45% since the start of the year, while Nutrien Ltd. (NTR) is up 20%. These companies are major nitrogen-based fertilizer makers and compete most directly with Middle Eastern imports.  

However, one company has barely risen 7% since January:   

The Mosaic Co. (MOS).   

The Florida-based firm is North America’s largest producer of potash and phosphate. In fact, it produces roughly 12% and 10% of the global output of these two nutrients. 

Now, these two fertilizers are slightly different from the nitrogen-based types that the Gulf states export. So, the stock has barely risen since January. 

Think of fertilizers like a three-legged stool. Each type represents a different leg, and you need all three to produce a stable crop. It’s why you’ll often see the “N-P-K” acronym on fertilizer bottles, and why fertilizing a lawn without soil testing first is a recipe for disaster. 

In theory, these three nutrients are not interchangeable. 

However, different crops need different amounts of N-P-K. Corn requires more nitrogen, while soybeans rely on far less. So, high prices in one type of nutrient can often cause shifts in what farmers plant.   

That’s why shares of Mosaic should soon rally. Farmers are very sensitive to price inputs, and rising nitrogen fertilizer prices will trigger a stampede into crops like soybeans. One researcher at the University of Arkansas’ System Division of Agriculture is already predicting 3.5 million acres of soybeans this year – a level not seen since 2017. 

We’re also fast approaching the start of the U.S. planting season. So, even if nitrogen-based fertilizers are allowed past the Hormuz Strait within the next several weeks, many American farmers will have already locked in their potash and phosphate demand for the whole year. 

In addition, MOS shares are relatively cheap. The stock trades at just half of long-term, midcycle valuations, and so even a return to normalcy gives shares a 2X upside. A windfall from higher fertilizer prices will only add to that.   

In other words, even if Middle East conflict suddenly ends and we see a deluge of Gulf region products back on world markets, it would be too late for farmers in the Northern Hemisphere to switch back to nitrogen-based crops. MOS remains a top pick in Fry’s Investment Report, and you can get more ideas like this by clicking here. 

2 Oil Stocks in the Wings 

The global energy crisis is real. The oil trade is obvious. And obvious trades are usually already priced in.  

This week’s wild reversals prove that point.  

Many speculators piled into oil futures at $120 per barrel… only to see prices fall below $80 within days. They’re now sitting back near $90, as if calling for traders to try again.  

But there are far better ways to invest in this market. Eric has two key picks in oil and gas in his Fry’s Investment Report portfolio. The first company is at the forefront of America’s shale revolution, and the recent jump in global oil prices now gives it another leg of growth.  

Here’s the fundamental case.  

Eric’s first energy pick is one of America’s largest shale oil producers. The firm completed a merger in early 2026 and now produces 1.6 million barrels of oil equivalent per day – enough to fill up 4.5 million cars with gasoline.  

It is also a relatively efficient producer, especially compared to global averages. The company’s breakeven oil price sits at just $44 per barrel and could reach the low-$40 range on post-merger cost savings. Even with oil prices pulling back, this means the company is still printing money and can still lock in $70-plus prices in the futures market.  

It’s a guaranteed profit either way.  

His second pick is in natural gas… and a company that’s quietly dominating the European landscape. Last week, Qatar was forced to shut liquefied natural gas (LNG) production after missile attacks from Iran began targeting energy infrastructure. The country makes up 20% of global LNG exports, and prices in East Asia and Europe have already spiked.  

What’s worse, sources say it would take at least a month to return to normal production volumes… which might not happen for a while. After all, LNG tankers are essentially floating bombs.  

That has had an immediate impact on European gas prices, which must compete with Asian buyers for supply. Dutch TTF Natural Gas Futures have spiked from $30 before the conflict to roughly $50… and could rise further as remaining winter stocks are depleted.   

Meanwhile, Eric’s top European gas pick sits at a valuation that doesn’t reflect its situation. Prices continue to trade almost 20% below their 2022 peaks.  

That gives it a solid double-digit upside from here.  

I must also note that the company is astonishingly well run. Production grew 3.4% to record levels in 2025, and management expects another 3% increase in 2026 with breakeven levels of $40/barrel equivalent. This represents a 25% rate of return at $65/barrel of oil.  

The company has a long history of managing windfall profits, and I expect shares to have double-digit upside from here. 

The Bottom Line 

No one can seem to agree where oil prices will go. 

Betting markets expect oil to retest the $110 level by June, while futures markets expect a steady decline to around $80. 

But Eric and I are not interested in making these kinds of 50-50 bets. Instead, we’re looking for investments with a greater guarantee of success, or those with such lopsided upside that the risks are worth taking.  

(With those sorts of speculations, Eric has made 41 stock recommendations that went on to gain 1,000%+… 14 that gained 2,000%+… seven that gained 5,000%+… and two that gained 10,000%+. It’s why he’s often been called “Mr. 1,000%.”) 

That’s why I think it’s so important that you learn more about these two winning-wager companies at Fry’s Investment Report.

If you join, you’ll also get immediate access to all of Eric’s research and portfolio picks, as well as his latest trade alerts and company updates.  

You can click here to learn more. 

And in the meantime, be sure to keep checking your email. We’ll be sure to think outside the box when it comes to oil stocks. All of Wall Street’s attention is now fixated on crude oil prices and every word the White House is saying about them.  

Take that opportunity to hedge with companies beyond their focus.  

Click here to become a member of Fry’s Investment Report today.

Until next time,  

Tom Yeung 

The post One Stock to Buy on Oil’s Wild Swings… and Two More in the Wings  appeared first on InvestorPlace.

Buy good companies. Diversify your portfolio. Stay the course. 

“Time in the market beats timing the market.”

It’s perhaps the single most repeated mantra in modern investing.

But the smartest money on Wall Street stopped relying on pure buy-and-hold years ago.

What replaced it – the strategy the quants, hedge funds, and institutional desks have migrated to over the past decade – is available to you right now. 

You just weren’t supposed to know about it…

Why Institutional Investors Rarely Use Pure Buy-and-Hold

If buy-and-hold is the optimal strategy, why don’t the best investors in the world use it?

Genuine buy-and-hold – investing in a diversified basket, ignoring the noise, rebalancing annually, holding for decades – is essentially what index funds do. And index funds have famously beaten the majority of actively managed funds over long periods. Warren Buffett has made this point so many times it has practically become investing gospel. So, the logical conclusion, if you follow the advice your broker gives you, is that nobody should be trying to beat the market. Just index and relax.

But here’s what’s actually happening with serious institutional capital…

Quantitative hedge funds – like Renaissance Technologies, Two Sigma, D.E. Shaw, and Citadel – are not managing diversified long-only portfolios and hoping for the best. They’re running sophisticated momentum- and pattern-recognition strategies, turning over positions at rates that would make many traditional investors’ heads spin. And the results speak for themselves.

Renaissance’s Medallion Fund, widely regarded as the most successful investment vehicle in modern financial history, has generated average annual returns north of 60% before fees for decades. Not by identifying undervalued companies and waiting patiently. By finding patterns in price behavior and trading them systematically.

Bloomberg reported that momentum traders are having their best run in three years. The biggest banks and asset managers have quietly built momentum factor exposure into their most sophisticated products. 

Eventually, academic finance caught up to what traders had already discovered.

Research going back to the early 1990s – including the landmark Jegadeesh and Titman momentum studies and later work incorporated into the Fama-French factor models – consistently found the same pattern: stocks that have been outperforming tend to keep outperforming for extended periods.

In other words, momentum isn’t a short-term anomaly. It is one of the most persistent return factors ever documented in financial markets.

Why Financial Advisors Still Recommend Buy-and-Hold

Whether you get advice from a financial advisor, a brokerage platform, or the endless stream of investing content online, the message is usually the same. 

Buy and hold. Stay diversified. Ignore the noise.

In reality, those recommendations are shaped as much by business models and compliance rules as they are by investment theory.

Most financial advisors and brokerage platforms operate within a compliance and liability framework that strongly favors passive, diversified, long-term strategies. The reason is simple: active strategies require judgment calls, and judgment calls create liability. If your advisor puts you in an index fund and the market drops 40%, that’s a market event – nobody’s fault, nothing to litigate. If your advisor recommends a more active, momentum-based approach that requires buying and selling based on price signals, every transaction is a potential compliance flag; every loss a potential complaint.

Beyond liability, there’s the asset-under-management model itself. 

Advisors are compensated based on how much money they’re managing on your behalf – typically around 1% of assets per year. That fee structure is maximized when you keep your money with them, invested, all the time. An active strategy that moves in and out of positions, holds cash during dormant periods, and prioritizes capital preservation as much as capital appreciation? That’s bad for assets under management (AUM) fees. “Sit tight and trust the process” is not just advice. It’s a revenue model.

And then there’s institutional inertia. 

The buy-and-hold narrative has been the backbone of retail financial advice for 50 years. It’s in the training materials, compliance manuals, client presentations. It took decades for alternative strategies to gain academic credibility, and academic credibility takes even more time to filter down to the advisor sitting across from you at a conference table. By the time something is safe enough for a compliance department to sanction, the sophisticated money has already been doing it for a generation.

Stage Analysis: The Framework Behind Momentum Investing

So, what exactly has Wall Street’s smarter money migrated toward? At its core, it’s a discipline that goes by various names – momentum investing, trend following, breakout trading. But all share a common ancestor: the recognition that stock prices tend to move through identifiable stages, and that the single most important skill in investing is knowing which stage a stock is in.

Trading pioneer Stan Weinstein popularized this framework decades ago in his book Secrets for Profiting in Bull and Bear ÃÛÌÒ´«Ã½s. Weinstein illustrated that every financial asset – every stock, index, and commodity – cycles through four distinct phases, and that most investors lose money primarily because they don’t know which phase they’re in.

Once you understand this framework, the market begins to look very different.

Stage 1: Consolidation

After a decline, a stock enters a dormant period, trading sideways in a narrow range, with low volume and indifferent or negative sentiment. This is dead money territory. You could own a Stage 1 stock for two years and go nowhere. Most retail investors who “buy the dip” end up camping here, waiting for a recovery that takes far longer than they expected.

Stage 2: Breakout and Momentum

This is the only stage that matters for generating returns – when price breaks decisively above the Stage 1 range, typically on expanding volume, with institutional accumulation driving the move. The breakout is the signal. Once a stock is in Stage 2, it tends to trend higher persistently, sometimes for months, even years. The gains aren’t evenly distributed across time. They’re front-loaded into the Stage 2 phase – and investors who miss the entry miss the bulk of the opportunity. 

A recent example illustrates how this works in practice. Kratos Defense (KTOS) entered a Stage 2 breakout in mid-2023. Our Breakout Trader system alerted us early, and we bought in at $13.57. Today, KTOS trades around $90 – and our subscribers are up more than 460% in the position.

This is stage analysis working exactly as designed.

Stage 3: Distribution

Eventually, the advance loses steam. The smart money that rode Stage 2 begins quietly selling, and price action becomes choppy and erratic. The headlines remain bullish – this is typically when a stock gets the most mainstream attention. But the underlying structure is deteriorating. This is the stage where retail investors, finally feeling confident enough to buy, are essentially purchasing shares from the institutional investors who’ve been selling for weeks.

Stage 4: Decline

The selling becomes obvious, sentiment collapses, and the stock surrenders its gains. Retail investors who bought in Stage 3 experience the full downside while the institutional money that identified the Stage 2 entry has long since moved on to the next opportunity.

The investing prescription is almost deceptively simple: buy Stage 2. Sell Stage 3. Never hold through Stage 4.

What makes this framework so powerful in today’s market – where algorithms now account for the majority of trading volume, retail emotion amplifies moves in both directions, and geopolitics can trigger a flash crash before you’ve finished reading the headline – is that it is entirely agnostic about why prices are moving. You don’t need to predict earnings or the Fed’s next move. You don’t need to have an opinion about whether AI is overhyped or undervalued. Just read the price structure and position accordingly.

That’s exactly what the hedge funds and quant shops figured out. Their competitive advantage isn’t a better view on company fundamentals – it’s better, faster, more systematic pattern recognition in price behavior.

Using Systematic Screens to Find Stage-2 Breakouts

If this framework has existed for decades, why hasn’t every investor adopted it? Because doing it properly, at scale, is brutally difficult by hand.

There are more than 5,000 publicly traded stocks in the U.S. market alone. Screening each one for Stage 2 setups – evaluating price relative to key moving averages, assessing volume patterns, scoring the quality of the breakout – requires either an enormous time commitment or a team of analysts. The institutional players have entire technology stacks devoted to this problem. The retail investor has a brokerage account and a finite number of hours in the evening.

That asymmetry is largely structural. The edge in stage analysis comes from identifying setups early – before they’re obvious, the mainstream money has piled in, and the stock is on the front page. If you’re running manual scans on a handful of stocks you already know about, you’re perpetually late.

The solution is a systematic, algorithmic screener that applies stage analysis across the entire market instantaneously – surfacing Stage 2 breakout candidates before they move, graded by the quality of the setup, available to any investor who knows where to look.

That’s exactly what we’ve built. 

Our latest breakout system grades every stock in the market from 0 to 5 based on the strength of its Stage 2 setup – the same analytical framework the smart money uses, automated so you can deploy it at market speed. In internal backtesting, it flagged eight of the top-performing stocks of 2025 before their major moves began… 

Hycroft Mining (HYMC) before a 1,100% run. Terns Pharmaceuticals (TERN) before an 865% surge. MP Materials (MP) nearly a full year before Pentagon and Apple deals sent it to the moon.

Your broker isn’t going to offer you this. The traditional advisory industry simply isn’t built to deliver it. But the strategy is real. The track record is documented. And the smart money has known for years. 

Now you do, too.

See exactly how the system works – and which stocks it’s flagging right now.

The post What Smart Money Knows and a Broker Would Never Tell You appeared first on InvestorPlace.

As we were going to press yesterday afternoon, President Donald Trump suggested the fast-moving U.S.–Iran conflict could soon wind down – though his comments also made clear the military campaign may not be finished.

Speaking at a press conference on Monday, Trump said the U.S. is closing in on its objectives after more than a week of strikes coordinated with Israel:

We’re achieving major strides toward completing our military objective…

We could call it a tremendous success right now…or we could go further, and we’re going to go further.

The president struck a careful balance in his remarks, signaling that the war may end soon while also warning that the U.S. could escalate further if necessary.

At one point, Trump described the conflict as “very complete, pretty much.” But moments later, he hinted the mission could continue beyond the initial military strikes. After being asked why Pentagon officials say the conflict is just beginning, Trump replied that “it’s the beginning of building a new country.”

So, while the military phase of the conflict may be nearing its end, the geopolitical consequences could drag out much longer.

The market reaction to Trump’s comments Monday was immediate – and enormous

Wall Street had opened in full risk-off mode as investors grappled with the possibility of a longer war, a deeper oil shock and another inflation scare.

But sentiment flipped after Trump suggested the conflict could be nearing its end, helping spark a sharp reversal in stocks. By the close, the S&P 500 had rebounded from an intraday drop of as much as 1.5% to finish up 0.8%, while the Dow rose 239 points and the Nasdaq gained 1.4%.

The gains are holding as I write on Tuesday in the early afternoon. All three major indices are in the green and were recently trading at their intraday highs.

But the far bigger reaction yesterday and today has come from oil.

As I noted in yesterday’s Digest, at its high on Sunday, crude surged above $115 a barrel.

Yesterday, prices initially eased when G7 energy ministers signaled they were preparing to step in if necessary.

Let’s go to our hypergrowth expert Luke Lango in yesterday’s Innovation Investor Daily Notes:

The G7 convened an emergency summit to discuss a coordinated SPR release – specifically, a 400-million-barrel release from their collective strategic reserves, a jaw-dropping 33% drawdown of the total 1.2 billion-barrel G7 stockpile (which would be the largest coordinated release ever). 

Oil fell from $120 to $100. 

The next leg lower in prices came later in the day after Trump’s comments – he even floated the possibility that the U.S. might take control of the Strait of Hormuz to secure shipping lanes.

By late Monday afternoon, crude had plunged dramatically from those weekend highs.

And as I write on Tuesday, West Texas Intermediate Crude (WTIC) has fallen to $84 while Brent Crude is down to $88.

Part of the decline reflects this morning’s meeting between G7 energy ministers. They confirmed they’re ready to release strategic oil reserves if necessary, though they have not yet triggered a final decision to open the tap.

Meanwhile, the International Energy Agency (IEA) will hold a meeting later today to discuss the release of oil stockpiles.

In short, some of the panic that gripped energy markets over the weekend is beginning to fade.

Stepping back, the speed of the recent price changes in oil underscores just how sensitive global markets remain to developments in the conflict – and why oil, more than any other asset, has become the real-time barometer of how serious investors believe the crisis could become.

And that’s exactly why what happens next in the oil market matters so much…

What if this war doesn’t end soon

While markets are currently betting on de-escalation, a lot is riding on how quickly this conflict actually winds down.

If oil doesn’t keep falling – or worse, reverses and heads higher – the economic consequences could spread far beyond energy markets.

To see why, let’s go back to Luke from yesterday’s Daily Notes.

He ran the numbers on what sustained triple-digit oil could mean for inflation. His conclusion isn’t pretty:

By my analysis, if oil prices stay around $100 and flow through into higher commodity prices across the whole supply chain (measured by Bloomberg’s Commodity Index ex Gold staying around $80 to $90, versus sub-$70 just a few weeks ago), then we are looking at potential 4-5% inflation in the coming months.

That’s the nightmare scenario policymakers – and investors – desperately want to avoid.

Remember, the Federal Reserve has spent the past two years trying to push inflation back toward its 2% target. A sustained oil spike would reverse much of the progress we’ve made.

Energy is one of the fastest ways inflation spreads through the economy. Higher oil means higher gasoline prices, higher shipping costs, higher airline fares, and more expensive goods across the entire supply chain.

Plus, if inflation suddenly starts climbing again, potentially moving into the 4%-5% range, the Fed might be forced to raise rates. That’s not a scenario Wall Street is pricing for the next 12-24 months. So, if that becomes a real possibility, we’re likely in for a violent market reaction.

Back to Luke:

It is SO IMPORTANT that oil prices get back below $80.

Because sustained oil prices >$100 and inflation back at 5% in this environment would lead to multiple “bubbles” popping at once (AI spending would slow, housing market would break, PE market would break, consumer credit market would break, etc.).

That’s how you kill a bull.

So, with crude back to $84, investors are breathing easier. But from here, it’s follow-through that matters.

Target on the Fed

Heading into this latest flare-up in the Middle East, the market had been steadily pricing in the next phase of the Fed cycle – interest rate cuts.

But sustained triple-digit oil prices would dramatically complicate that outlook.

As I write, the CME Group’s FedWatch Tool shows that traders are betting on a July rate cut – the probability of at least a quarter-point reduction is roughly 59%.

These probabilities have shifted significantly. One month ago, traders put nearly 85% odds on at least a quarter-point cut in July.

Much of that shift reflects the spike in oil prices and renewed fears that inflation could reaccelerate if the conflict drags on.

Right now, the chief concern is “higher for longer.” In other words, if inflation reaccelerates due to sustained higher oil prices, the Fed may have very little choice but to keep monetary policy tighter for longer.

But as we noted earlier – and what Luke fears – oil at $100+ puts hikes on the table.

The key point here is that markets aren’t pricing that outcome right now.

Despite the geopolitical turmoil of the past week, investors are currently betting that the spike in oil will prove temporary – not the start of a new inflation cycle.

That’s why the sharp drop in crude prices over the past 48 hours has mattered so much.

If oil stabilizes somewhere in the $80–$90 range, the broader inflation outlook probably doesn’t change much. The Fed can stay on its current path, rate cuts later this year remain plausible, and the bull market likely stays intact.

But if crude suddenly reverses and pushes back toward $100, that’s when things could change quickly.

And the past few days have shown just how quickly sentiment in the oil market can swing.

Three signals investors must watch…

First, whether the conflict itself actually begins to cool…

It’s one thing for political leaders to talk about winding the war down. It’s another thing entirely to see the violence truly de-escalate – fewer strikes, calmer rhetoric, and a clear path toward ending the fighting.

If bombs keep falling and tensions remain high, markets will likely continue pricing in the risk of supply disruptions.

Second, oil prices themselves…

If crude keeps trending toward $80, the inflation scare fades quickly. The bull comes roaring back. If not, uncertainty lingers, and today’s market gains reverse.  

Third, inflation data in the weeks ahead – but not with tomorrow’s CPI report, which won’t reflect this oil spike.

Bottom line: If higher energy costs begin bleeding into broader commodity prices and transportation costs, we’ll start seeing it show up in inflation reports – and the Fed will notice. For now, though, markets appear to be betting that the worst-case scenario won’t happen.

So, oil is falling… stocks are rebounding… and investors are cautiously returning to risk assets.

The next few weeks will determine whether that bet proves right.

We’ll keep you updated here in the Digest.

Have a good evening,

Jeff Remsburg

The post Oil’s Plunge Sends a ÃÛÌÒ´«Ã½ Signal appeared first on InvestorPlace.

Stocks move faster than they used to. It’s common now to see big swings – sometimes 30% or more – even in companies that are doing well.

My friend and colleague Luke Lango believes this is the result of deeper changes in the market. Algorithms, high-frequency trading, and heavy retail participation have made volatility a regular part of investing.

In the essay below, Luke explains why these shifts matter and how investors can look for stocks that may be ready to move higher.

He also explains the approach in a free presentation, where he walks through the system his team uses to scan thousands of stocks for potential breakouts.

You can watch the full presentation here.

Now, here’s Luke…

**

There’s a quiet panic spreading through the investing world.

It doesn’t show up in headlines. But you hear it in planning offices and investor forums:

“Why doesn’t this make sense anymore?”

It’s that moment when your watchlist is green at 10:30… red by lunch… and back to flat by the close — and you can’t even point to a single piece of news that explains the entire round trip.

Or when a stock reports “good” earnings, sells off anyway, then rips higher two days later — not because anything changed in the business, but because money moved.

That disconnect is what’s unnerving people. Not volatility by itself… but volatility that feels unmoored, like the market is reacting to forces most investors can’t see.

The media focuses on AI companies and job disruption. But the deeper shift is happening inside the market itself.

Stocks move faster. They reverse harder. And they disconnect from fundamentals more violently than at any point in modern history. The strategies that built wealth for decades can still work — but they no longer work the way investors remember.

ÃÛÌÒ´«Ã½s that once moved in days now move in minutes. Sometimes seconds.

“Buy great businesses and wait” still works over long stretches. But it now requires enduring drawdowns many investors simply can’t stomach.

Algorithms are now the market.

They account for roughly 70% to 90% of daily U.S. equity volume. Add a surge in retail participation — with stock cash flows running more than 50% higher last year — and you get a system wired for speed and sharp swings.

The human beings you picture on a trading floor — reading tape, making calls, “deciding” what happens next — are mostly the last visible layer of the system.

The real decision-making is increasingly automated, happening in data centers where machines react to headlines, prices, and order flow faster than any person can process.

That doesn’t mean “humans don’t matter.” It means the first move often happens before humans even agree on what the story is.

The average holding period has collapsed from roughly eight years in the 1950s to about five months today.

Since COVID, we’ve experienced three bear markets — roughly one every two years.

That’s not a temporary phase. It’s structural.

And it may intensify. ÃÛÌÒ´«Ã½s are evolving beyond rule-based algorithms toward agentic AI systems that react to data — and to one another — in real time.

So what happens when price and fundamentals drift apart?

Blue-chip stocks like Netflix Inc. (NFLX) and Nvidia Corp. (NVDA) have lost 35%, 50%, even 60%+ before recovering.

Nvidia alone has endured four major crashes in eight years. The stock ultimately advanced — but holding through those drops required unusual discipline.

Most investors don’t “just hold.” They sell low and buy back higher. Loss aversion is powerful — and expensive.

Meanwhile, price behavior has grown increasingly detached from business performance. Opendoor Technologies Inc. (OPEN) rallied nearly 1,900% in two months despite deteriorating fundamentals.

Zillow Group Inc. (Z), another real estate tech firm with stronger revenue and market position, barely moved.

When price decouples from fundamentals, traditional analysis becomes unreliable.

Here’s how you operate in a market like this…

Stage Analysis: Built for Fast ÃÛÌÒ´«Ã½s

In a high-volatility environment, valuation alone isn’t enough. What matters is where capital is flowing now.

That’s the foundation of stage analysis, popularized by Stan Weinstein.

Every stock moves through four recurring stages:

• Stage 1: Sideways consolidation
• Stage 2: Breakout and sustained advance
• Stage 3: Distribution
• Stage 4: Decline

Stage 2 is where the money is made.

Palantir Technologies Inc. (PLTR) moved from $9 to over $200 after entering Stage 2.

Carvana Co. (CVNA) surged more than 6,000% from its breakout.

Stage analysis doesn’t forecast earnings. It identifies when accumulation is already happening and momentum is building.

In a market defined by rapid rotations, recognizing a Stage 2 breakout early can mean the difference between chasing a move and positioning ahead of it.

The Real Problem: You Can’t Do This Manually

There are thousands of publicly traded stocks. At any moment, a small number are transitioning from consolidation into breakout mode.

That’s where major gains begin.

You won’t catch them by flipping through earnings reports or waiting for a TV segment. By the time they trend on social media, the move is already underway.

That’s why my team built a systematic breakout screener, which I reveal during my new free broadcast. It scans more than 3,000 stocks and assigns each a 0-to-5 breakout score based on momentum strength.

In historical testing, it flagged eight of 2025’s top-performing stocks before their major advances — including:

• Hycroft Mining Holding Corp. (HYMC) before a 1,100% run
• Terns Pharmaceuticals Inc. (TERN) before an 865% surge
• And Palantir long before it became a mainstream AI story

The objective is simple: identify stocks as institutional momentum builds — when price and volume confirm something meaningful is happening.

Volatility isn’t going away. Leadership will continue to rotate quickly.

You can try to keep up manually.

Or you can use a system designed for the market we actually have.

In my latest free presentation, I walk through how it works, what Stage 2 looks like on a chart, and which stocks are scoring highest right now. I give the name and ticker of one of those stocks away for free. Plus, folks who join me will gain unlimited access to my new breakout stock screener, which they can use to find their own Stage 2 stocks.

The market won’t slow down.

But you don’t have to fall behind.

Sincerely,

Luke Lango

Editor, Hypergrowth Investing

The post Why “Just Hold” Doesn’t Feel Safe Anymore appeared first on InvestorPlace.

1. What Is the Strait of Hormuz and Why Does It Matter to Investors?

The Strait of Hormuz sits between Iran and the Arabian Peninsula — and war there has shaken global energy markets. The waterway is a critical passage for oil and LNG exports, and when it’s disrupted, the effects don’t stop at crude. They ripple into natural gas, fertilizer, and agricultural markets that most investors aren’t watching.

See which stocks to buy during the Hormuz crisis — and why. →

2. Should I Buy Oil Stocks Now or Did I Miss the Move?

The obvious trade has already proved dangerous. Oil nearly reversed 30% in a single session on Monday — a reminder that trading crude during a geopolitical crisis is closer to a coin flip than an investment.

The producers worth owning are a different kind of bet entirely — ones that stay profitable whether oil is at $85 or $120.

See which stocks to buy during the Hormuz crisis — and why the crude trade misses the point. →

3. Is Devon Energy (DVN) Stock a Buy During the Hormuz Crisis?

Devon is one of America’s largest shale producers and recently merged with Coterra Energy. Its breakeven oil price is low enough that it remains profitable even as crude pulls back — and it can lock in current prices in the futures market regardless of where spot oil goes.

But Devon isn’t purely an oil story. A stranded gas problem in West Texas that hobbled Devon for years is now resolving, with new pipeline capacity coming online that connects its production to LNG export facilities on the Gulf Coast — just as global LNG supply has tightened.

Get the complete Devon Energy (DVN) stock analysis for the Hormuz crisis. →

4. Is Equinor (EQNR) Stock a Buy During the Hormuz Crisis?

Equinor is Europe’s largest supplier of piped gas — and it has been here before. When Russian gas supplies dried up after the 2022 Ukraine invasion, Equinor stepped into the vacuum. Shares roughly doubled and dividends grew for four consecutive years.

Qatar has now been forced to curtail LNG production following Iranian missile strikes on its energy infrastructure. European gas prices have already spiked in response. Equinor shares are still trading nearly 20% below their 2022 peak.

Get the complete Equinor (EQNR) stock analysis for the Hormuz crisis. →

5. Should I Buy Mosaic (MOS) Stock During the Hormuz Crisis?

The Gulf isn’t only an energy hub — it’s a major supplier of nitrogen-based fertilizers, and those exports have effectively stopped. The most direct beneficiaries have already moved: CF Industries is up over 40% since January, Nutrien is up 20%.

Mosaic produces potash and phosphate — a different category — which is why it hasn’t moved with them. But rising nitrogen prices are already starting to influence crop planting decisions, and that ripple has implications for Mosaic that Wall Street hasn’t fully caught up to yet.

Get the complete Mosaic (MOS) stock analysis for the Hormuz crisis. →

6. What Are the Risks If the Hormuz Crisis Resolves Quickly?

Oil prices are unpredictable in both directions. But Devon and Equinor’s low breakeven costs mean they remain profitable even if crude pulls back sharply. And the fertilizer market shift behind the Mosaic thesis is a separate dynamic from the oil price entirely.

See the complete Hormuz crisis stock analysis for Devon, Equinor, and Mosaic. →

Thomas Yeung is a market analyst and portfolio manager of the Omnia Portfolio, the highest-tier subscription at InvestorPlace. He is the former editor of Tom Yeung’s Profit & Protection, a free e-letter about investing to profit in good times and protecting gains during the bad.

The post 3 Stocks to Buy During the Hormuz Crisis — and Why appeared first on InvestorPlace.

Wall Street didn’t wait for the morning shows. It didn’t wait for analysis. It didn’t even wait for traders to wake up.

Within milliseconds, trading algorithms had already processed the headlines, recalculated risk, and started selling.

By the time most of us saw “U.S.-Israel strikes Iran” on our phones, equity futures were sharply lower, oil was spiking, and volatility was jumping.

No panic on a trading floor. No shouting brokers.

Just machines.

This is how markets work now. Wars don’t slowly ripple through investor psychology anymore. They hit the wires – and algorithms pull the trigger. 

More than 70% of U.S. equity trades are now executed by algorithms (and in certain high-frequency windows, that figure approaches 90%).

At the same time, retail participation has surged, with brokerage cash flows jumping more than 50% last year.

Fast machines. Record individual participation.

That combination creates a market that feels jumpier than ever.

I hear it from readers all the time: “I’m doing everything right… and it still feels like I’m one bad afternoon away from losing months of progress.”

That anxiety is real – and rising.

Just look at the extremes:

• Netflix Inc. (NFLX) down 75% in six months… 
• Bill Ackman reportedly losing $400 million on that trade in three months… 
• And a profitless “meme” stock like Opendoor Technologies Inc. (OPEN) rallying 900% while stronger peers finished the year down.

No wonder investors feel on edge.

So, what’s the answer?

Not prediction or panic.

A process.

Treat volatility as information, and then focus on the one signal that tends to survive chaos: breakouts.

The opportunity isn’t in reacting to headlines. It’s in recognizing when a stock quietly shifts from consolidation into momentum, before the crowd shows up.

That’s what we’ll walk through next…

Why Stock ÃÛÌÒ´«Ã½ Volatility Is Increasing

Volatility doesn’t care about your retirement timeline.

It doesn’t care how “strong” the fundamentals look on paper.

When missiles strike while we sleep, the algorithms start firing before most investors have poured their first cup of coffee.

And just like that, months of steady gains can evaporate in an afternoon.

If your strategy depends on markets moving calmly and gradually, you have a problem.

Yet momentum traders are having their best stretch in years. Study after study shows momentum strategies tend to outperform over time.

The reason is simple.

You’re not predicting the future.

You’re reading the present.

But spotting genuine momentum before it becomes obvious requires more than instinct. It requires a system.

Stage Analysis: The Smartest Framework for Volatile ÃÛÌÒ´«Ã½s

In 1988, trading pioneer Stan Weinstein outlined a framework in his book, Secrets for Profiting in Bull and Bear ÃÛÌÒ´«Ã½s, that changes how you see stock charts.

His thesis: Every asset moves through four stages.

• Stage 1: Sideways consolidation, largely ignored.
• Stage 2: Breakout and sustained advance.
• Stage 3: Distribution, as smart money exits.
• Stage 4: Decline. 

The money is made in Stage 2.

Consider a few examples…

Palantir Technologies Inc. (PLTR) entered Stage 2 in May 2023 around $9. By late 2025, it traded above $200.

Carvana Co. (CVNA) broke into Stage 2 at nearly $7 in May 2023. It climbed more than 6,500%.

The investors who caught those moves didn’t need insider information. They recognized the Stage 2 setups before the rest of the market showed up.

That’s the power of stage analysis.

A System That Identifies Breakout Stocks Early

Identifying true Stage 2 breakouts across thousands of stocks before they move requires serious analytical horsepower.

That’s why my team and I have built a system that quantifies Weinstein’s framework into a proprietary scoring model – grading thousands of stocks in the market from 0 to 5 based on the strength of their momentum setup.

In back-testing, it flagged eight of 2025’s top-performing stocks before their big runs, including:

• Hycroft Mining Holding Corp. (HYMC) before a 1,100% move.
• Terns Pharmaceuticals Inc. (TERN) before an 865% surge.
• Western Digital (WDC) and Palvella Therapeutics (PVLA) before 460%-plus increases.

The system doesn’t chase headlines.

It looks for one thing.

Stocks on the verge of entering Stage 2.

In a market driven by algorithms and geopolitical shocks, reading price structure instead of predicting headlines isn’t optional. 

It’s essential.

The Bottom Line: Volatility Is the New Normal

AI has fueled a powerful bull market. But history shows late-stage rallies can accelerate – and then reverse just as quickly.

That doesn’t mean you sit on the sidelines.

It means you use the right tools while the opportunity is still there.

Volatility isn’t going away.

Geopolitical shocks aren’t going away.

Algorithms aren’t going away.

But chaos always produces outliers – stocks entering stealth bull markets while the rest of the headlines scream crisis.

The question is whether you have a way to find them.

In my latest free presentation, I explain why the old playbook no longer works… and what’s replacing it.

You’ll see how volatility has become the new normal… why buy-and-hold now feels like a white-knuckle ride… and how my Stage 2 breakout strategy is designed to target stocks just as major momentum runs begin.

I’ll walk you through the four-stage framework, show you how my upgraded Nexus Stock Screener analyzes more than 3,000 stocks in seconds, and reveal the name and ticker of a stock the system just flagged.

If you’re tired of reacting to market chaos, and ready to get ahead of the next major move, this broadcast is for you.

Click here to watch it now.

The post The ÃÛÌÒ´«Ã½ Has Changed… Have You? appeared first on InvestorPlace.

Editor’s Note:  As we’re going to press, headlines report that President Donald Trump has said the war with Iran could be nearing its end.

Trump told a CBS News reporter that “the war is very complete, pretty much.” He went on to say that the U.S. is “very far” ahead of schedule in its stated timeframe for military initiatives.

In response, the major stock indexes are rebounding while oil pulls back. 

We’ll address this in tomorrow’s Digest. Below is our analysis of the markets before this last-minute headline.  One thing is for sure – expecting and preparing for volatility is more important than ever.

As I write Monday morning, markets are volatile after oil prices spiked over the weekend.

The U.S. benchmark, West Texas Intermediate crude, and the European benchmark, Brent crude, briefly surged to around $115 per barrel Sunday amid fears of escalating conflict in the Middle East and potential disruptions to global supply.

Prices have since pulled back to roughly $96 for WTI and $99 for Brent, but the sudden spike was enough to rattle investors and inject fresh volatility into global markets.

Behind the turbulence is a Middle East conflict that shows no signs of easing. Oil tanker traffic through the vital Strait of Hormuz – a key artery for global energy shipments – has slowed dramatically, threatening to choke off one of the world’s most important oil supply routes.

Let’s jump to legendary investor Louis Navellier with some of the latest developments:

The new leader of Iran, the Ayatollah’s son, apparently, has already been injured already in an airstrike. That comes from an Israeli source.

Meanwhile, Israel hit some oil tanks in Tehran.

That did get people nervous because I am not sure they want the oil infrastructure hurt. But Israel probably had their own reasons for those particular tanker facilities.

Oil prices eased from Sunday’s spike largely on reports that G7 finance ministers were preparing to discuss a coordinated release from strategic petroleum reserves to stabilize markets.

That meeting has now taken place, but no coordinated release was announced (as I write). Even so, crude prices have continued to cool from their weekend highs.

Still, the rollercoaster has Wall Street rattled. Earlier today, all three major U.S. indexes were down more than 1% as oil fears hit the market. Stocks have since stabilized and even attempted a rebound, underscoring just how volatile trading has been.

Though they’ve pulled back from those levels, the broader trend still has them hovering near a critical technical test.

What will happen at the 200-day MA?

At the end of last week, in his Innovation Investor Daily Notes, our hypergrowth expert Luke Lango noted that the major indexes are now trapped between two critical technical levels.

As Luke explained:

The S&P 500, Dow, and Nasdaq are currently stuck between their 100-day and 200-day moving averages.

That’s no-man’s land in technical analysis — a zone famous for chopping up both bulls and bears before the market makes a decisive move in either direction. 

Luke wrote that this could work out two ways in the short term:

ÃÛÌÒ´«Ã½s rarely put in durable bottoms in the middle of that range.

They tend to either reclaim the 100-day on positive momentum, or flush down to test the 200-day and bounce.

Both setups are actionable. Neither has arrived yet.

Since Luke’s analysis, stocks initially moved lower on this morning’s oil fears, pushing the indexes closer to the “flush” scenario he described. As I noted earlier, they’re off their lows, but still approaching the 200-day MA.

So – at least for the moment – markets appear to be testing the downside of that range.

As you can see below, the Nasdaq has fallen below its 50- and 100-day Moving Averages (MAs) in blue and red.

This morning, it hit its 200-day MA in green but has since rallied – and is even trying to turn positive on the day as I write.

The S&P and the Dow are also approaching their 200-day MAs.

Now, even before this morning’s selloff, Luke was recommending caution. But with the major indexes flirting with this key technical level, he’s also watching closely for a potential tradeable bounce – particularly in AI infrastructure stocks, which he’s been pounding the table on over recent weeks.

Back to Luke:

The trade we want is clear. AI infrastructure names were sold on a thesis that the data is now actively disproving.

Know what you want to own. Know the prices you’d pay. Know what catalyst you’re waiting for — [potentially] a 200-day bounce with a reversal candle.

Be ready to move fast when it arrives.

To be clear, if the indexes don’t find support at their respective 200-day MAs, we’re going lower. So, continue to factor “defense” into your positioning for the moment.

But if we hold and bounce at support, it could be a fantastic entry point for some of the stocks on your watchlist.

This “wait and see” advice echoes Luke’s trading philosophy

There’s a core principle that guides Luke’s approach to short- and medium-term trading…

Price is truth.

In a world where economic data, headlines, and forecasts constantly shift, price action cuts through the noise.

After all, if a stock is rising, that’s what matters for your portfolio – not what an analyst thinks should be happening. And if a stock is falling or simply moving sideways in a choppy range like today, that message matters just as much.

This “let price lead” philosophy sits at the heart of a market framework known as stage analysis.

At its core, stage analysis simply recognizes that every stock tends to move through four phases during its life cycle:

The biggest gains tend to occur during Stage 2, when heavy buying pressure drives a sustained upward move.

But even strong Stage-2 advances rarely move in a straight line. Pullbacks and volatility are normal along the way. What matters is whether the broader trend remains intact. And that’s exactly what Luke is watching right now.

Returning to today’s market setup, if the S&P bounces at its 200-day MA on strong volume and pushes back toward its 100-day MA, that would signal renewed momentum – with many potential trade entry opportunities.

But if not, and we lose the 200-day MA, the S&P would likely fall to the 6,521 – 6,550 zone, which represents the October/November 2025 lows. 

With stage analysis, you’re not frontrunning or guessing about what will happen at these levels. You’re simply letting price lead the way.

So, until we see the first signals of which way the S&P wants to break – evidenced through price – stage analysis suggests waiting right now. That’s exactly what Luke is doing.

He’s identifying the companies he wants to own… determining the prices he’s willing to pay… and waiting for the market to confirm that the next trend has begun.

For more on exactly how this process works, Luke recently released a presentation explaining his stage-analysis framework in detail.

In it, he walks through how to identify stocks entering Stage 2… how to avoid those slipping into Stage 4… and even a company currently sitting closest to potential breakout territory.

You can watch it right here.

Returning to the oil and gas sector

One week ago today, we put the United States Oil Fund (USO) on your radar as a way to play the spike in oil prices.

If you bought in, congratulations, you’re up 23%.

But be careful about buying today.

For more on this, let’s go to Brian Hunt, editor of Money & Megatrends:

After sprinting flat out for more than a month, the oil sector is due for well-deserved rest.

Behind Brian’s call is simple mean reversion.

This is the idea that after a financial instrument has experienced a large move in one direction and is in an abnormal state, it is likely to “revert” to a more normal state.

Brian likens stocks to runners, noting “they can’t sprint flat out for miles at a time. They need to take breaks… or ‘breathers’.”

But Brian’s call isn’t just about mean reversion. He highlights a political angle:

The White House is fully aware that Operation Epic Fury could have painful “bad domino effects.”

Epic Fury is raising oil prices… which could raise American gasoline prices… which could hurt the Republican party during the mid-term election season.

There is enormous incentive for Trump to end this quickly and let the markets calm down.

Now, Brian is quick to say that anything is possible with Trump. But still, if you’re sitting on a huge pile of overnight cash from this trade, taking a few dollars off the table isn’t a bad idea.

Back to Brian:

The odds favor a big correction in oil and oil stocks soon.

One more thing investors are watching – the labor market

Finally, don’t forget the other macro development investors began digesting late last week.

On Friday, the Labor Department reported that the U.S. economy lost 92,000 jobs in February, a headline that initially rattled markets.

Now, the report wasn’t quite as bad as it looked. A large healthcare strike and severe winter weather both distorted the data, temporarily dragging down payrolls.

Even so, the numbers reinforced a broader trend: the labor market appears to be gradually cooling. And this raises an important question we’ll tackle in a coming Digest.

With oil prices spiking while the labor market slows, the Federal Reserve finds itself in a difficult position. Rising energy prices tend to push inflation higher, but a cooling job market could argue for lower interest rates.

That’s a difficult combination for policymakers…

The Fed typically raises interest rates to combat inflation but cuts rates to support a weakening labor market. However, oil-driven inflation and slowing job growth would pull those tools in opposite directions.

So, what will the Fed do?

We’ll dig into this soon.

Coming full circle

Investors are dealing with several crosscurrents right now.

Oil prices have surged on geopolitical fears… major indexes are testing key technical support levels… and the broader economic picture remains uncertain as the labor market cools and policymakers weigh their next move.

This uncertainty can feel uncomfortable for investors, but it’s also part of how markets transition from one trend to another.

For now, the smartest approach may be the same one Luke is following: let price reveal the market’s next move – but be ready to act once it does.

We’ll keep you updated here in the Digest.

Have a good evening,

Jeff Remsburg

The post Keep Your Eyes on This Level appeared first on InvestorPlace.

As a result, crude oil prices reached over $110 per barrel over the weekend, a level not seen since the early months of the Russian invasion of Ukraine in 2022. As I write this, prices are about $100 per barrel.

Uncertainty over how long this crisis could last has made investors nervous – and that uncertainty continues to weigh on the broader market.

So, in this week’s ÃÛÌÒ´«Ã½ Buzz episode, my friend and MoneyFlows co-founder Jason Bodner joins us to talk about the ongoing Iran conflict, how past geopolitical events have impacted the markets and what investors should do.

We also discuss the recent rebound in software stocks and what the latest economic data signals for the economy. Plus, Jason shares three of his top stock picks right now.

Click the image below to watch now.

If you’d like to learn more about Jason, check out his website here. You can also find his YouTube channel, Money Flows, here.

To see more of my videos, click here to subscribe to my YouTube channel.

Plus, the grades in Stock Grader (subscription required) have been updated this week! Click here to plug in your own stocks and see how they’re rated.

Why AI Will Continue to Move the ÃÛÌÒ´«Ã½

During today’s ÃÛÌÒ´«Ã½ Buzz, Jason also pointed out that while geopolitical events may create short-term volatility, they rarely change the long-term forces driving the market.

I agree, which is why I believe the rapid expansion of artificial intelligence will continue to move the market.

Big tech companies are racing to build the infrastructure needed to power the next generation of AI systems – from advanced chips to massive new data centers.

This race could reshape entire industries… and create significant opportunities for investors who understand where the technology is headed.

That’s why I recently recorded a special presentation explaining what I believe could be the next major chapter in the AI Revolution – and the company I believe sits at the center of it.

Click here to watch the full presentation now.

Sincerely,

Louis Navellier

Editor, ÃÛÌÒ´«Ã½ 360

The post Iran Crisis Shakes ÃÛÌÒ´«Ã½s: 3 Top Stock Picks Right Now w/ Special Guest Jason Bodner appeared first on InvestorPlace.

Hearing that there’s “no end in sight” to the current U.S.-Iran war might not comfort investors – but that’s exactly how one Iranian official recently described it to CNN.

ÃÛÌÒ´«Ã½s have already felt the turbulence, and aluminum is no exception.

The metal surged almost 10% last week, hitting a three-year high as the conflict disrupted aluminum shipments from the Persian Gulf. The region supplies roughly 9% of global aluminum, so prices spiked quickly on supply fears – before an even more recent selloff brought them back down.

If the war continues to create a global aluminum shortage, mining companies could stand to benefit. Now, I am certainly not celebrating conflict in the Middle East; but we can only invest in the world as it is, not in the rose-tinted world we might prefer.

In the real world, tighter supply usually means higher prices.

And beyond the escalating conflict, aluminum demand has increased thanks to AI’s need for infrastructure and hardware.

Think of AI infrastructure like a living body: If power is the blood circulating through data center infrastructure, metals are the bones.

In effect, every ton of metal pulled from the ground is a claim on the AI buildout.

Unlike software vendors or chip designers, metals companies don’t need to guess which AI model wins or which agent framework dominates. They just need to deliver the raw materials that make the entire ecosystem possible.

Aluminum demand is accelerating. Every high-voltage line that feeds an AI data hub consumes one to two tons of aluminum per megawatt delivered. Each new stretch of long-distance transmission deepens the world’s appetite for this versatile metal. From 104 million tons of demand in 2024 to an estimated 120 million by 2030, global aluminum consumption is set to grow relentlessly.

That spells good news for one of my Fry’s Investment Report holdings: Alcoa Corp. (AA), the largest U.S.-based aluminum producer.

Toward the end of 2025, Alcoa’s prices reached a new three-year high. After suffering a tariff-induced selloff earlier in the year, Alcoa’s shares have been trending higher.

I expect that uptrend to gain momentum – driven not only by firmer aluminum prices, but also by the company’s exceptional fundamentals.

Alcoa is not just the largest American aluminum producer, but it is also among the world’s most environmentally progressive. Producing aluminum requires immense amounts of electricity, and that energy intensity is reshaping the industry.

Today, renewable energy powers roughly 87% of Alcoa’s smelting operations and about 70% of Norwegian aluminum company Norsk Hydro’s (NHYDY). This alignment with the global push toward decarbonization gives both companies a durable strategic advantage, and positions them not merely as metal producers, but as critical enablers of the cleaner, more electrified world AI will depend on.

In the end, the market may reward not those who build the virtual world, but those who power it. The AI Revolution will always need its dreamers, but it will depend on the miners that turn metal into its bones.

In the race for AI supremacy, the hyperscalers may scorch their balance sheets, but the miners will still be cashing the checks. While hyperscaler shareholders wrestle with wafer-thin cash cushions and swelling debt, metals firms operate with clearer economics.

Their business models are not theoretical. They are measurable and proven.

Therefore, for investors seeking exposure to the AI Revolution without betting on which form of intelligence will win, a mining company like Alcoa offers a compelling opportunity.

For more information on what makes this stock a “Buy,” click here to learn how to join me at Fry’s Investment Report.

Now, let’s take a look back at what we covered here at Smart Money. Then, I’ll let you in on another way to profit in today’s unpredictable, high-pressure market.

Smart Money Roundup

The ÃÛÌÒ´«Ã½ Moves in Four Stages — Here’s When to Move With It

March 4, 2026

According to InvestorPlace Senior Analyst Luke Lango, market volatility is now the default, and focusing on a stock’s valuation alone is no longer enough. In Wednesday’s essay, Luke discusses his perspective further, explaining why market phases are structural – and how to invest in the stage we’re in now, where momentum can majorly enhance returns. Click here to read more.

The Stock Everyone’s Buying That AI Will Destroy

March 5, 2026

As the market is surrounded by unpredictability, we’d rather focus on the foreseeable: the world-changing transformations happening thanks to artificial intelligence. AI’s takeover is inevitable – we’re already seeing it reshape industries like law, healthcare, and accounting. And soon, it will target another industry most investors don’t even suspect is vulnerable. Read on to discover the company Tom Yeung believes AI will disrupt, and how to invest in the businesses most likely to survive.

Big Tech Takes the AI Bill: What It Means for Investors

March 7, 2026

Last week, a septet of Big Tech companies signed a “Ratepayer Protection Pledge” – a pledge aimed at preventing passing AI data center-related electricity costs on to households. However, given a history of AI infrastructure driving higher electricity bills, it’s still unclear how these companies will be held to their promise to now bear those costs. Click here for more details on what this means for investors, and how to get in early on the best opportunities.

70% of Trades Are Now Machines. Here’s How to Beat Them.

March 8, 2026

In today’s market, the “buy great companies and wait” approach only works for investors with iron stomachs and patience for long holding periods. The biggest gains now tend to come in short, powerful bursts. And for Luke Lango, that’s helped shape his breakout system, allowing investors to profit from quick-moving stocks. Read on to learn more about how to implement Luke’s strategy.

Looking Ahead

The markets are feeling the pressure of rapid changes, leaving many investors unsettled.

That’s why I not only want to share one of my favorite stocks with you today – but also give you the opportunity to learn more about my colleague Luke Lango’s approach for navigating this volatile environment.

In Luke’s brand-new video, he lays out why volatility isn’t fading anytime soon… why the old buy-and-hold playbook is struggling in this environment… and how he designed a momentum-driven “Stage 2” approach in order to target stocks as they begin major breakouts.

He also walks through real historical examples his system flagged early — before some of the biggest runs of the past few years.

Plus, during the event, he reveals a free breakout stock pick you can look into immediately.

If you haven’t watched yet, now is the time.

Regards,

Eric Fry

The post As This Metal’s Prices Rise, This Company Stands to Profit appeared first on InvestorPlace.

This Week’s Ratings Changes:

Upgraded: Strong to Very Strong

Downgraded: Very Strong to Strong

Upgraded: Neutral to Strong

Downgraded: Strong to Neutral

Upgraded: Weak to Neutral

Downgraded: Neutral to Weak

Upgraded: Very Weak to Weak

Downgraded: Weak to Very Weak

To stay on top of my latest stock ratings, plug your holdings into Stock Grader, my proprietary stock screening tool. But, you must be a subscriber to one of my premium services.

To learn more about my premium service, Growth Investor, and get my latest picks, go here. Or, if you are a member of one of my premium services, you can go here to get started.

Sincerely,

Louis Navellier

Editor, ÃÛÌÒ´«Ã½ 360

The post NVIDIA Upgraded, Eli Lilly Downgraded: Updated Rankings on Top Blue-Chip Stocks appeared first on InvestorPlace.

It doesn’t show up in headlines. You won’t hear it on CNBC. But it’s there — in financial planning offices, in investment forums, even inside earnings calls.

It sounds like this:

“Why doesn’t this make sense anymore?”

You probably think it’s about AI. That part is obvious. The media is fixated on who will win the AI arms race, how many jobs will disappear, and which companies will dominate the next decade.

But that’s not the real disruption.

The deeper shift is already happening – inside the market itself.

Stocks now move faster, reverse harder, and disconnect from fundamentals more violently than at any point in modern history. The strategies that built generational wealth over the last fifty years still can work… but they no longer work the way investors remember.

A century ago, the ticker tape compressed Wall Street into minutes. Then came computers, program trading, and the quant revolution. Today, the next compression is happening in microseconds. 

If you’ve felt that whiplash, you’re not alone.

The market can surge 2% before lunch, plunge by the close, then erase the entire move the next morning… often without a headline large enough to explain it. The traditional advice to “own great businesses and wait” can still work over long stretches of time. But it now requires sitting through drawdowns that most people struggle to endure.

This is because algorithms dominate today’s markets. But that’s only half the story. The truth is, they are today’s markets. 

Estimates suggest they account for roughly 70%–90% of daily U.S. equity volume. Layer in a surge of retail capital – with cash flows into U.S. stocks running 53% higher in 2025 than the year before – and you get a system wired for speed, emotion, and sudden air pockets.

The human beings you picture on a trading floor, reading tape and making calls, are largely set dressing at this point. The real action is happening at the speed of light, in server farms in New Jersey, running models that have read more earnings transcripts and analyzed more price patterns than any human team could in a thousand lifetimes.

Even time horizons have compressed. The average holding period has fallen from roughly eight years in the 1950s to about five months today.

Bear markets that once arrived roughly once a decade are appearing far more frequently. Since COVID, we’ve experienced three, or roughly one every two years.

I can hear folks saying, “That’s not normal!”

But it is the new normal today. 

And the next phase may bring even more instability. ÃÛÌÒ´«Ã½s are moving beyond algorithms that execute predefined strategies toward AI systems that make decisions, adapt to new data, and respond to one another in real time. If volatility feels embedded today, further acceleration is likely.

So what do you do when price and fundamentals drift apart? When blue-chip stocks such as Netflix (NFLX) or Nvidia (NVDA) routinely lose 35%, 50%, or 66% of their value before recovering, what does it mean?

For many investors, the cost of staying the course has become too much to bear. 

So, in today’s issue, I’ll explore a framework that can help trade this market: stage analysis, popularized by Stan Weinstein. I’ll explain why “Stage 2” – when a stock breaks out of quiet consolidation into a sustained advance – is where the most meaningful gains often begin.

You’ll also see why identifying these setups manually across 5,000-plus stocks is unrealistic, and how a systematic breakout scoring approach can help surface potential Stage-2 candidates before they become front-page stories.

Why Buy-and-Hold Breaks Down In Volatile ÃÛÌÒ´«Ã½s

AI’s impact on markets as a trading tool, where algorithms execute predefined strategies at machine speed, is only the first phase…

The next phase is already taking shape, and it is far more consequential.

AI agents – autonomous systems capable of making decisions, adapting to new information, and acting without direct human instruction – are moving from research labs into real-world deployment. 

And their influence on markets is still underappreciated.

Imagine portfolio systems that no longer wait for quarterly meetings to rebalance. They adjust continuously, reacting in real time to earnings releases, macro data, price shifts, and even one another’s behavior. 

Imagine exchange-traded funds (ETFs) managed by adaptive agent systems that rotate in and out of positions dynamically based on live pattern recognition. 

Now consider the feedback loops that emerge when these systems respond not only to market conditions but to the reactions of other AI systems… cascades of automated decision-making unfolding in fractions of a second.

We have already seen how coordinated algorithmic behavior can trigger flash crashes, liquidity vacuums, and sharp price dislocations. Expanding that framework to smarter systems managing larger pools of capital suggests an environment where volatility becomes even more embedded.

The average stock holding period has already collapsed from roughly eight years in the 1950s to about five months today. In an agent-driven market, that compression is likely to continue.

Long-term investors will have to compete against systems that process and act on information in microseconds. Holding a stock for years while waiting for fundamentals to assert themselves becomes increasingly difficult in an environment defined by rapid rotations and frequent drawdowns.

The stress this creates is not theoretical. It shows up in real portfolios.

Nvidia (one of the most wealth-creating stocks of the past decade) declined 56% in 2018, 3% in 2020, 66% in 2021–2022, and 37% in early 2025. 

That is four 35%-plus crashes in just eight years, or about one every two years. The stock ultimately recovered and advanced, but enduring those losses required unusual discipline.

But the academic version of “stay invested” glosses over the lived experience of watching a third (or half) of your wealth evaporate and being told “this is fine, this is normal, just hold…”

Most people don’t hold. 

They sell at the bottom and buy back near the top, which is why retail investors chronically underperform the indices they’re theoretically tracking. This response is rooted in human psychology. Losses register more intensely than equivalent gains.

At the same time, the relationship between fundamentals and price has become less reliable as a short- to medium-term guide. Opendoor (OPEN), despite deteriorating revenue and margins, rallied near-1,900% in little more than two months. 

Zillow (Z), with record revenue and a dominant market position, gained less than 30% over the same period and finished the year down 7%.

When a stock’s price has effectively decoupled from its business performance, fundamental analysis becomes a map to a territory that no longer exists.

Stage Analysis: The Framework Built for This World

In a high-volatility, momentum-driven market, valuation alone isn’t enough. What matters most is where real money is flowing in real time.

That’s the foundation of stage analysis, first systematized by trading pioneer Stan Weinstein in “Secrets for Profiting in Bull and Bear ÃÛÌÒ´«Ã½s.”

The thesis is elegant in its simplicity: every stock moves through four recurring stages.

• Stage 1: Consolidation – a long, quiet sideways base after a decline.
• Stage 2: Advancing – the breakout phase, when institutional money steps in and the price begins a sustained move higher.
• Stage 3: Distribution – momentum stalls as early buyers start taking profits.
• Stage 4: Decline – selling accelerates and the cycle resets.

The opportunity is concentrated in one phase: Stage 2.

It’s almost insultingly simple once you see it: buy Stage-2 breakouts, sell when Stage 3 begins, and avoid everything else.

This is where Palantir moved from a single-digit stock to a triple-digit stock…

Where Carvana (CVNA) exploded more than 6,000% off its lows…

Where major advances begin (often before the headlines catch up).

Stage analysis doesn’t try to forecast earnings or guess fair value. It identifies when accumulation is already underway and momentum is building.

In today’s market, where leadership rotates quickly and volatility is constant, recognizing a stock entering Stage 2 can make the difference between chasing a move… and getting positioned early.

In a moment, I’ll show you how we apply this framework across more than 3,000 stocks – and how it’s helping surface potential breakouts before they become apparent to everyone else.

The Problem: You Can’t Do This by Hand at ÃÛÌÒ´«Ã½ Speed

To sum it up, the market you learned to invest in no longer exists.

When 70%–90% of daily volume is driven by machines… when retail capital can flood in with a swipe… when leadership rotates in weeks instead of years… it can be expensive to hesitate.

There are thousands of publicly traded stocks in the U.S. market. At any given moment, a small handful are quietly transitioning from Stage 1 to Stage 2… from sideways action into sustained advances.

That transition is where the biggest gains tend to begin.

You won’t consistently find those names by flipping through earnings reports on a Saturday afternoon. You won’t catch them by waiting for a TV segment. And once they’re trending on social media, the breakout is already well underway.

That’s why we built a systematic Stage-2 breakout screener that scans more than 3,000 stocks and assigns each a 0-to-5 breakout score, based on the strength of its momentum setup.

In historical testing, it identified eight of 2025’s top-performing stocks before their major advances began.

It flagged Hycroft (HYMC) before a 1,100% run.

Terns (TERN) before an 865% surge.

And, again, Palantir (PLTR), long before it became one of the most talked-about AI stocks in the market.

The goal is simple: identify stocks as institutional momentum builds, when price and volume confirm that something meaningful is happening.

Volatility is part of the landscape now. Leadership changes quickly. Capital moves fast.

You can try to keep up manually, sure. And I wish you good luck. Or… you can use a system built for this environment.

See how it works by viewing my urgent presentation today.

You’ll see what Stage 2 looks like on a chart.

And you’ll learn which stocks are scoring highest in our system right now.

The market won’t slow down, but you don’t have to fall behind.

The post AI Is Killing Buy-and-Hold Investing. Here’s What Replaces It. appeared first on InvestorPlace.

In this environment, “buy great companies and wait” strategies can work… but they require iron stomachs and long holding periods. Meanwhile, the biggest gains tend to come in short, powerful bursts… when a stock shifts from quiet consolidation into momentum.

That’s what today’s essay explores. I’ve invited my colleague Luke Lango to explain why today’s volatility is structural, why the old rules don’t apply, and how identifying “breakout” stocks can dramatically improve your odds.

In his latest free briefing, Luke reveals how historical analysis shaped a breakthrough system designed to identify some of the fastest-moving stocks in the market — before their biggest runs begin. The same framework identified stocks ahead of gains of 2,623%, 865%, and 2,149%… and it just flagged four stocks that could be on the verge of a major rally. (He reveals one for free during his latest broadcast.)

If you’ve been feeling the market’s whiplash, this is a strategy built for this kind of environment. Read on…

On Saturday, February 28, at roughly 9 a.m. in Tehran, explosions lit up the Iranian capital.

Wall Street didn’t wait for the morning shows. It didn’t wait for analysis. It didn’t even wait for traders to wake up.

Within milliseconds, trading algorithms had already processed the headlines, recalculated risk, and started selling.

By the time most of us saw “U.S.-Israel strikes Iran” on our phones, equity futures were sharply lower, oil was spiking, and volatility was jumping.

No panic on a trading floor. No shouting brokers.

Just machines.

This is how markets work now. Wars don’t slowly ripple through investor psychology anymore. They hit the wires — and algorithms pull the trigger.

More than 70% of U.S. equity trades are now executed by algorithms (and in certain high-frequency windows, that figure approaches 90%).

At the same time, retail participation has surged, with brokerage cash flows jumping more than 50% last year.

Fast machines. Record individual participation.

That combination creates a market that feels jumpier than ever.

I hear it from readers all the time: “I’m doing everything right… and it still feels like I’m one bad afternoon away from losing months of progress.”

That anxiety is real — and rising.

Just look at the extremes:

• Netflix Inc. (NFLX) down 75% in six months…
• Bill Ackman reportedly losing $400 million on that trade in three months…
• And a profitless “meme” stock like Opendoor Technologies Inc. (OPEN) rallying 900% while stronger peers finished the year down.

No wonder investors feel on edge.

So what’s the answer?

Not prediction. Not panic.

A process.

Treat volatility as information, and then focus on the one signal that tends to survive chaos: breakouts.

The opportunity isn’t in reacting to headlines. It’s in recognizing when a stock quietly shifts from consolidation into momentum, before the crowd shows up.

That’s what we’ll walk through next…

Chaos Is an Asset Class… If You Have the Right Map

Volatility doesn’t care about your retirement timeline.

It doesn’t care how “strong” the fundamentals look on paper.

When missiles strike while we sleep, the algorithms start firing before most investors have poured their first cup of coffee.

And just like that, months of steady gains can evaporate in an afternoon.

If your strategy depends on markets moving calmly and gradually, you have a problem.

Yet momentum traders are having their best stretch in years. Study after study shows momentum strategies tend to outperform over time.

The reason is simple.

You’re not predicting the future.

You’re reading the present.

But spotting genuine momentum before it becomes obvious requires more than instinct. It requires a system

Introducing Stage Analysis: The Hidden Architecture of Every Stock

In 1988, trading pioneer Stan Weinstein outlined a framework in his book, Secrets for Profiting in Bull and Bear ÃÛÌÒ´«Ã½s, that changes how you see stock charts.

His thesis: Every asset moves through four stages.

• Stage 1: Sideways consolidation, largely ignored.
• Stage 2: Breakout and sustained advance.
• Stage 3: Distribution, as smart money exits.
• Stage 4: Decline.

The money is made in Stage 2.

Consider a few examples…

Palantir Technologies Inc. (PLTR) entered Stage 2 in May 2023 around $9. By late 2025, it traded above $200.

Carvana Co. (CVNA) broke into Stage 2 at nearly $7 in May 2023. It climbed more than 6,500%.

The investors who caught those moves didn’t need insider information. They recognized the Stage 2 setups before the rest of the market showed up.

That’s the power of stage analysis.

A System That Does the Work for You

Identifying true Stage 2 breakouts across thousands of stocks before they move requires serious analytical horsepower.

That’s why my team and I have built a system that quantifies Weinstein’s framework into a proprietary scoring model – grading thousands of stocks in the market from 0 to 5 based on the strength of their momentum setup.

In back-testing, it flagged eight of 2025’s top-performing stocks before their big runs, including:

• Hycroft Mining Holding Corp. (HYMC)before a 1,100% move.
• Terns Pharmaceuticals Inc. (TERN) before an 865% surge.
• MP Materials Corp. (MP) months before the Pentagon deal and a partnership with Apple Inc. (AAPL) sent it to the moon.

The system doesn’t chase headlines.

It looks for one thing.

Stocks on the verge of entering Stage 2.

In a market driven by algorithms and geopolitical shocks, reading price structure instead of predicting headlines isn’t optional.

It’s essential.

The Window Is Open, but It Won’t Stay That Way

AI has fueled a powerful bull market. But history shows late-stage rallies can accelerate – and then reverse just as quickly.

That doesn’t mean you sit on the sidelines.

It means you use the right tools while the opportunity is still there.

Volatility isn’t going away.

Geopolitical shocks aren’t going away.

Algorithms aren’t going away.

But chaos always produces outliers – stocks entering stealth bull markets while the rest of the headlines scream crisis.

The question is whether you have a way to find them.

In my latest free presentation, I explain why the old playbook no longer works… and what’s replacing it.

You’ll see how volatility has become the new normal… why buy-and-hold now feels like a white-knuckle ride… and how my Stage 2 breakout strategy is designed to target stocks just as major momentum runs begin.

I’ll walk you through the four-stage framework, show you how my upgraded Nexus Stock Screener analyzes more than 3,000 stocks in seconds, and reveal the name and ticker of a stock the system just flagged.

If you’re tired of reacting to market chaos, and ready to get ahead of the next major move, this broadcast is for you.

Click here to watch it now.

Regards,

Luke Lango

Editor, Hypergrowth Investing

The post 70% of Trades Are Now Machines. Here’s How to Beat Them. appeared first on InvestorPlace.

In 2015, I visited the observatory at One World Trade Center – the newly opened viewing deck on the Western Hemisphere’s tallest building. 

When I got up to the 100th floor, people on one end of the deck began smiling… murmuring… pulling out their phones and craning their necks. 

Then others joined in. Slowly at first… and then faster as news spread across the room. 

Arnold Schwarzenegger had also decided to show up that day. 

Now, economic theory would have said the crowd’s slow reaction was impossible. In a perfect world, information flows instantaneously. Everyone in the room should have known the moment the first person caught a glimpse. 

But we all know things don’t work that way. Not everyone knows everything at once. In fact, the person who left the observatory five seconds earlier may never have known The Terminator star had shown up. 

I tell you this because information on Wall Street flows the same way. 

Corporate insiders and perfectly timed Polymarket betters always seem to be the first to act.

Then comes early birds (industry watchers and Wall Street analysts). Next there’s the early crowd… the mass market… and then finally the latecomers and bag-holders. 

All this is why market momentum exists. Buying builds up as information spreads.

That’s how you end up with breakout stocks, like the ones Senior Analyst Luke Lango identifies. These are companies that have seen some initial interest from people… and are ready to surge as the crowd joins in.

He illustrates this with Apple Inc. (AAPL), where a Stage 1 consolidation in 2015-2017 (during peak iPhone fears) gave way to a Stage 2 advancement as service growth drew in early buyers… followed by a Stage 3 breakout once everyone else caught on Investors who held through the initial +83% rise would have seen +300% returns by the end of 2020. 

It’s a pattern that happens repeatedly. And once you have a system that identifies when these breakouts happen… well… that’s when you stop buying stocks that go nowhere and start buying stocks that seem to rise immediately. 

Today, I’d like to share two stocks that demonstrate the power of Luke’s Breakout System – companies with hidden catalysts that could be entering the early stages of a major move. 

If you’d like to see exactly how Luke identifies these opportunities, check out Luke’s latest presentation on his Breakout System. In a brand-new video, where he explains how his Nexus Breakout Screener helps pinpoint stocks poised to move higher. 

So, let’s get started… 

The Biotech Bet 

Last November, I showed you Greenwich LifeSciences Inc. (GLSI) here after the company’s key person, CEO Snehal Patel, began buying up stock. The biotech firm had passed several critical clinical trial hurdles and was selling at a deep discount for owning a proven clinical-stage therapy. 

Shares have since tripled in price. (Note: I have since moved GLSI to a “sell” based on risk vs. price.) 

Now, Luke’s Nexus Breakout Screener has helped me identify a new biotech pick. And it’s a firm that’s entering the most catalyst-dense period in its operating history: 

Larimar Therapeutics Inc. (LRMR). 

The $550 million market-cap company is working on a drug for a rare disease called Friedreich’s ataxia (FA), an inherited neurogenerative disorder that (unlike Parkinson’s or ALS) begins affecting younger people between ages 5 and 15. As many as 26,000 people worldwide are thought to have it. 

Currently, there is only one approved therapy for FA on the market – a drug owned by Biogen Inc. (BIIB) that charges $370,000 yearly per patient. It now generates over $500 million in annual sales, despite not being approved for children under 16. 

Larimar is hoping to change that. Its drug is seeking approval for people of all ages, and it more directly tackles the root cause of FA than Biogen’s Skyclarys. Early results released last September suggest Larimar’s version is even more effective than the existing market therapy. If approved, there’s a reasonable chance that it eventually becomes a global billion-dollar blockbuster. 

Most importantly for investors, Larimar is now entering the most catalyst-dense period in its history. 

In February, the firm’s FA candidate achieved Breakthrough Therapy designation, adding to a list of other accelerated regulatory programs. It also completed a capital raise. This “stacking” strategy means Larimar is guaranteed to report its clinical trial results in June 2026 and kickstart an expedited approval process soon after. As a result, the company is now on a relatively clear track towards a potential approval decision by H1 2027 – long before it can run out of cash. 

Of course, the opportunity comes with risk. Like many small biotech firms, Larimar’s future hinges on the success of a single drug candidate; investors remain cautious after earlier safety concerns and the relatively small size of its clinical trials. The current trial is also small, given the rarity of FA. In other words, this remains a high-risk, high-reward setup where shares could surge 3X if upcoming data is positive, as I expect, or fall sharply if last September’s results were somehow incorrect. 

However, the risks are not enough of a concern for Larimar’s largest financial backers either, who collectively bought almost $26 million of the Philadelphia-area company’s stock in the past week during its late February secondary offering. Given the company’s adequate cash and unusually clear June 2026 catalyst, it’s no wonder LRMR scores a stunning 4 out of 5 in Luke’s Nexus Breakout Screener. Expect an inflection point in the next three months, and a roughly 80% chance of good news (vs. market-priced 30% chance). Shares are likely worth closer to $15 than its current $5 price. 

The AI-Resistant Play 

Last week in Fry’s Investment Report (subscription required), I warned that streaming firm Netflix Inc. (NFLX) is surprisingly exposed to the same AI “SaaSpocalypse” that has crushed many software-as-a-service (SaaS) firms. And that brings me to today’s second recommendation from Luke’s Nexus Breakout Screener: 

Gray Media Inc (GTN). 

The 80-year-old firm is America’s third-largest TV station operator, with 180 stations across 113 markets. It is the largest group owner and operator of NBC-affiliated stations and scores a perfect 5 out of 5 points in Luke’s Nexus Breakout Screener this week. 

So, how does a company in a “dying” cord-cutting market have such a perfect breakout score under its belt? 

Let me explain by turning back to Netflix. 

In short, Netflix’s moat comes from making engaging, high-quality video content that users happily pay $17.99 a month to access. These are beautifully crafted shows like The Crown and Stranger Things… with the occasional flop thrown in. 

But what happens when AI-generated video becomes good enough to compete? 

That will quickly destroy Netflix’s moat. Suddenly, the streaming giant will be forced to contend with talented individuals using AI to write movie screenplays, design live-action characters, draft detailed storyboards, and eventually create feature-length films… right in their bedroom. 

“But AI video is slop,” some might counter. “And what about all the errors we see in today’s models?” 

Well, that’s exactly what everyone said about AI-generated software too, before GPT-5 and Claude 4.6 became able to write working code. I expect Netflix to eventually face the same existential crises that have pummeled software firms. 

Now, here’s the thing: 

Netflix’s bosses aren’t stupid. 

They know that digital content creation (besides sports and perhaps live news) will soon face AI competition. In fact, Netflix is aggressively integrating generative AI in its own content and pursuing multimillion-dollar sports deals. 

They also realize their path to survival will hinge on distribution.  

No matter how beautiful an AI-generated movie becomes, no one will see it until it’s uploaded to a visible space like YouTube, Netflix, or cable TV. 

That’s why I believe Netflix’s bosses were so keen on overpaying for Warner Bros. Discovery Inc. (WBD). Not only would they receive film and TV studios (plus valuable intellectual property), but the deal would have also included cable and TV channels like CNN, Discovery, TNT Sports, and Cartoon Network, as well as a movie distribution network. 

It’s also probably why shares of Gray Media have risen 25% in the past month. Gray operates one of the few AI-resistant corners of the media world, and early-bird investors are beginning to notice. Luke’s Breakout Screener system certainly did. 

So, even if Netflix doesn’t end up trying to own TV stations outright (which it still might), there are plenty of other investors who will soon realize what the streaming company’s bosses already know. 

The Catalyst-Driven Investor 

The real takeaway of this week’s update isn’t just these two tickers. It’s the process of finding them. We know that news spreads… slowly at first… and then faster until the whole room is craning its neck. That’s true for spotting Arnold Schwarzenegger, and it’s also true for finding the next big investment. Those who can see the trend early will be the ones to benefit. 

That’s why I want to once again urge you to watch Luke’s latest free presentation on trading “breakout” stocks. He lays out the Stage 2 framework behind these ideas, and explains how you can use his Nexus Breakout Screener to get volatility to work with you in identifying perfect moments to jump in. 

Check it out here.

And I’ll see you back at the Digest next Sunday. 

Until next week, 

Thomas Yeung 

ÃÛÌÒ´«Ã½ Analyst, InvestorPlace

Thomas Yeung is a market analyst and portfolio manager of the Omnia Portfolio, the highest-tier subscription at InvestorPlace. He is the former editor of Tom Yeung’s Profit & Protection, a free e-letter about investing to profit in good times and protecting gains during the bad.

The post 2 Breakout Stocks to Buy Immediately   appeared first on InvestorPlace.

Yes, these days, AI plays a part in our military, too. 

Last Saturday, the world woke to news that Iran’s supreme leader, Ayatollah Ali Khamenei – the architect of proxy wars across the Middle East and the man who built Iran’s nuclear program – had been killed in a joint U.S.-Israeli precision strike in Tehran. 

And soon after, reporting revealed that Anthropic’s Claude AI had been used to support the operation. 

According to reporting from The Wall Street Journal, US Central Command used the AI for “intelligence assessments, target identification and simulating battle scenarios” during the strikes on Iran. What the U.S. is calling Operation Epic Fury was the kind of surgical, intelligence-driven operation that modern AI-powered targeting and analysis made possible.

It was one of the most dramatic geopolitical developments in years, executed with a precision that leaves no doubt: AI is not the future. It is the present.

And yet there is a strange disconnect between that reality and how most people invest. You almost certainly do not own a single share of the companies actually building the AI technology reshaping history.

Why Most Investors Still Don’t Own the AI Companies That Matter

Think about the last time you used AI. Maybe you asked ChatGPT a question, got Claude to help edit a document, or read Grok’s take on the news. Those models are three of the most powerful AI tools in the world – and the companies behind them are still private. 

OpenAI, Anthropic, xAI – not a share available on any exchange. 

And those are just the consumer-facing names. Behind the scenes, another firm – Anduril – is building the future of defense, centered on advanced autonomous systems. And, yes, it is private, too. 

AI is changing the world – but you don’t really own the AI that matters. 

Sure, many investors own shares of Nvidia (NVDA); maybe Microsoft (MSFT) or Amazon (AMZN). But none of them fully control the intelligence layer itself. 

Nvidia makes the chips those models run on. Microsoft distributes OpenAI’s technology under license. Amazon sells cloud compute. 

These are picks-and-shovels plays in the AI gold rush – excellent investments, but still indirect exposure. 

That means most investors have been participating in the AI revolution from the bleachers. But the insiders, founders, and venture capitalists… They have the field-level seats. They are the ones who will get phenomenally rich when these companies – the real AI pioneers like OpenAI, Anthropic, xAI, Anduril, etc. – go public.

Until now, there was nothing you could do about it. 

But everything changes here in 2026.

2026 Could Be the Year of the AI IPO

2026 is shaping up to be one of the most consequential years for technology IPOs in decades. Not because one great company is going public – but because several of them are.

OpenAI is preparing for an IPO that could potentially value it near the trillion-dollar mark – which would make it one of the largest technology IPOs ever attempted. The company generates over $20 billion in annualized revenue, growing at triple-digit rates, with 810 million monthly active users and 1 million enterprise customers. It just closed a funding round valued at $730 billion with backing from Amazon, SoftBank (SFTBY), Nvidia, and Microsoft. 

OpenAI is targeting a listing as early as Q4 2026. And Anthropic – the AI safety-focused lab backed by Google and valued at $380 billion – is also widely expected to explore a public listing.

The SpaceX–xAI Mega IPO and the Rise of AI Defense

But OpenAI and Anthropic are only the beginning here.

Elon Musk has assembled the most audacious corporate structure in modern tech. In February, he merged SpaceX – his aerospace company – with xAI to create a trillion-dollar conglomerate that combines the world’s leading orbital launch provider, a frontier AI lab, and the social media platform X. The combined entity is targeting an IPO potentially as early as June, at a valuation some sources put as high as $1.5 trillion. If you want to invest in the SpaceX IPO, you’re also buying xAI and X. It is, by design, the most vertically integrated technology company ever to approach public markets.

And then there’s the sleeper of the group: Anduril Industries. 

Founded in 2017 by Palmer Luckey – the same wunderkind entrepreneur who founded Oculus and sold it to Facebook at age 21 – Anduril builds systems traditional defense primes struggle to replicate: AI-native, software-first autonomous systems. Its Lattice OS platform serves as the operating system for autonomous military operations, integrating sensor data across every domain and coordinating weapons systems in real time. With revenue racing toward $2 billion, a valuation that has gone from $14 billion to more than $60 billion in under two years, a $1 billion advanced manufacturing facility coming online in Ohio, and a CEO who has publicly declared the IPO “definitely” coming, Anduril’s public market debut is only a matter of when, not if.

The 2026 AI IPO Bonanza is imminent – and it is going to be one of the most talked-about investment moments of our lifetimes.

Why Buying On IPO Day Rarely Delivers the Biggest Gains

Of course, investors could simply wait for these companies to go public and buy shares on IPO day. 

That is exactly what most people will do.

But history suggests that strategy rarely produces the biggest gains…

The first wave of internet IPOs in the late 1990s produced some of the most spectacular one-day pops ever recorded. 

But for most post-IPO investors, the years that followed were brutal. The insiders and venture capitalists who invested at pre-IPO valuations captured the overwhelming majority of the gains. The retail investors who piled in after the bell, swept up in the excitement, often held stocks that subsequently fell 50%, 70%, 90%.

The lesson wasn’t that the internet was a bad bet. Clearly, it wasn’t. 

The lesson was about when you got in. 

The early investors – those who bought in when the risk was high and the access was limited – captured the extraordinary returns. Those who got in after the world knew about it were, in many cases, left holding the bag during the inevitable post-IPO digestion.

Now apply that same framework to the AI era. 

OpenAI at a $1 trillion IPO valuation will be the most-hyped public offering in history. The institutional demand will be ferocious. The one-day pop could be enormous. And the question every investor should be asking is, “what will I be paying for it – and is that price better or worse than what I could have paid before the noise began?”

History shows the answer is obvious.

How Investors Can Access AI Companies Before They Go Public

It’s also important to note that the investment landscape has genuinely changed over the last few years – in a way that most investors have not fully processed.

A new category of investment vehicle has emerged. And it allows ordinary investors – not just hedge funds, accredited millionaires, or Silicon Valley venture insiders – to gain pre-IPO exposure to the world’s most transformational private companies. 

These vehicles trade like stocks. All you need are a ticker symbol and a brokerage account – no $250,000 minimum check, VC connections, three-year lockup period, or complex special purpose vehicle (SPV) paperwork required.

And most importantly, there are specific vehicles in this category that provide direct exposure to OpenAI, xAI, SpaceX, and Anduril right now, before they go public. 

These are not futures bets or derivatives or synthetic products. They are investment funds with actual positions in these private companies, wrapped in publicly traded structures and available to any investor with a standard account.

For the first time, you don’t have to be Sequoia Capital or Andreessen Horowitz to join the founding shareholder class of the most important technology companies being built today. 

The democratization of pre-IPO investing has arrived, without fanfare – which is exactly why most retail investors haven’t discovered it yet.

The Bottom Line

Artificial intelligence is rapidly becoming the foundational technology of the next economic era.

The companies building the core models, platforms, and autonomous systems that power it are still largely private.

But that window is beginning to close.

The venture capitalists who bet on these companies early are preparing to cash out at valuations that will make them unimaginably wealthy. And the founders are about to see their net worth go vertical. 

For the first time in the history of private technology investing, ordinary investors now have a legitimate mechanism to stand alongside them – before the IPO circus arrives, before the institutional allocations are spoken for, before the opening-day pop has already happened without you.

The 2026 AI IPO Bonanza is the financial story of the decade. The only question is which side of the velvet rope you’re standing on when the bell rings.

Want to learn exactly which investment vehicles offer pre-IPO access to OpenAI, SpaceX/xAI, and Anduril – and how to position yourself today? 

I just put together a full presentation on this topic, including a deep-dive analysis of each vehicle, the risks every investor needs to understand, and our specific recommendations. 

Click here to watch it now.

The post The OpenAI IPO Could Be the Biggest AI IPO Ever appeared first on InvestorPlace.

Typically, “bearing the cost” of a situation is not a coveted position.

Whatever the toll may be, if you have to foot the bill, it’s natural to prefer the shoe be on another foot. That is to say, nobody wants the responsibility of financial obligation.

That is, all but Big Tech.

On Wednesday, Big Tech companies signed a “Ratepayer Protection Pledge.” The goal is to prevent passing AI data center-related electricity costs on to households.

The seven major companies that signed the pledge are Amazon.com Inc. (AMZN), Microsoft Corp. (MSFT), Alphabet Inc. (GOOG), Meta Platforms Inc. (META), Oracle Corp. (ORCL), OpenAI, and xAI.

The septet is comprised of the biggest builders of AI infrastructure and data centers in the world. And their large-scale AI buildouts consume massive amounts of electricity.

This has put pressure on the electric grid and, in turn, hiked up electricity bills. But now Big Tech is prepared to bear the cost of its AI data centers. The shoe reportedly fits.

Whether this is a true Cinderella-story remains to be seen. It is so far unclear how Big Tech will be held to its promise.

But hyperscalers paying the power bill could give AI data centers the green light – and spark a boom for the backbone that makes AI run.

So, in today’s Smart Money, let’s take a look at costs that Big Tech has pledged to bear, investment opportunities that could follow, and the best way to get in early.

The High Cost of Data Centers

Data center deals alone hit record $61 billion in 2025, and Alphabet, Microsoft, Meta and Amazon spent around $350 billionon capital expenditures (CapEx). This massive investment was largely driven by AI infrastructure needs, including data centers.

This year, those same four hyperscalers are expected to spend nearly $700 billion.

The capital expenditures in projects like data centers by the five major hyperscalers now consume more than half of their pre-CapEx cash flow.

The popular storyline seems to be that these titanic investments, while onerous over the short term, will reap major benefits over the long term.

While that remains to be seen, there is no denying that data centers are already reshaping the national power grid.

A single hyperscale campus typically draws 50–100 megawatts (MW), the equivalent of tens of thousands of homes. Dominion Energy Inc. (D) serving Virginia’s “Data Center Alley,” forecasts 7 gigawatts (GW) of new demand by 2035 from data centers alone. That’s larger than the entire load of some regional utilities.

Looking nationwide, Bain & Company estimates that AI compute in the U.S. will require 100 GW of new power capacity by 2030, half of which will be in the U.S. That’s like adding the entire power generation capacity of South Korea in just five years.

More energy consumption means higher energy costs… and higher power bills.

According to the U.S. Energy Information Administration, data centers accounted for 4% of total U.S. electricity use in 2024. Future data usage is expected to increase 6-12% by 2028.

In the electricity market run by PJM Interconnection, which covers a large portion of the eastern United States, demand from new data centers has already begun pushing up power costs.

In the region’s 2025-26 “capacity market” (the advance payment to power plants to guarantee future electricity supply), data center demand drove an estimated $9.3 billion increase. As a result, monthly electricity bills could rise $18 in western Maryland and $16 in Ohio.

Americans may see more widespread price hikes in coming years. A study from Carnegie Mellon University estimates that data centers could lead to an 8% increase in the average U.S. electricity bill by 2030.

Hikes in energy prices have already caused public backlash against data centers.

In September 2025, Google dropped plans for a new data center in Franklin Township, Indiana, after residents organized a months-long campaign against the project. One of their biggest concerns was the potential rise in electricity costs for local households.

Big Tech’s “Ratepayer Protection Pledge” is aimed at drawing support from towns and cities, like Franklin Township, that oppose the foundational AI infrastructure.

And if local backlash is calmed, it could speed up approvals for new AI data center buildouts. The pledge could effectively give Big Tech a “social license” to expand, especially if the expansion doesn’t raise household electricity prices.

To restate, if the pledge produces concrete commitments or remains largely symbolic remains unknown, at least for now.  

But it could spell a bullish run for a specific group of stocks. And it’s best to get in early…

The Hidden Engine Powering Data Centers

More data centers means that the entire physical infrastructure behind AI – chips, electricity, servers, cooling – will benefit if construction accelerates.

These companies will be the obvious, and earliest, beneficiaries of AI data center expansion. But there is also one component that makes everything in the AI world work.

Without it, even the most powerful AI chip, including Nvidia is just expensive silicon.

See, when you build an AI data center, thousands upon thousands of servers must be installed.

But here’s the kicker: Those servers are useless unless they can talk to and learn from each other. And the way they communicate is through fiber-optic cables.

New AI hyperscalers need 10X more cables than regular data centers. That’s enough fiber to circle the globe eight times – in a single facility.

To harness that growth, I’ve got a pick that fits squarely in the category of stock I love the most – overlooked and underhyped.

This company quietly built the backbone of the internet, while scores of companies boomed and busted.

And now, as AI explodes, it is a leading supplier of what every data center desperately needs.

High demand means customers are inking deals with the company to reserve product ahead of time to edge out competitors. Already, 80% of the AI fiber-optic cable this company makes over the next five years is spoken for.

And it is manufacturing most of it right here in America. This means virtually no tariffs and no trade restrictions for its U.S. customers.

Here’s the best part…

While Nvidia’s biggest customers are turning into competitors, nobody is trying to manufacture their own optical-fiber cables. So, AI hyperscalers are all fighting to get more cables from this company, not replace them.

That’s continual, compounding reward.

I share the name of this company in my free, special broadcast. Click here to learn more.

Regards,

Eric Fry

The post Big Tech Takes the AI Bill: What It Means for Investors appeared first on InvestorPlace.

Before anyone had heard of ChatGPT or the AI revolution that has come to dominate the market, Nvidia (NVDA) was already a successful company best known for one thing: making explosions look better.

If you’ve ever played a modern video game, you’ve seen the result. A rocket slams into a building… the fireball blooms outward… debris scatters in every direction… and the entire scene unfolds as realistically as any Hollywood movie.

The visuals are powered by graphics processing unit (GPU) chips designed to perform thousands of calculations simultaneously. The GPUs enable games to render lifelike worlds in real time.

For most of its history, that was Nvidia’s business.

And it was very successful.

Its chips helped create more immersive games… better picture quality… and increasingly spectacular digital destruction.

Then, engineers realized something else.

The same chips they were using to simulate an explosion down to the smallest spark could also process enormous amounts of data at once. And that made them uniquely suited for a completely different task: training artificial intelligence.

Nvidia didn’t invent AI. But the chipmaker recognized earlier than almost anyone else that AI would require an entirely different kind of computing architecture.

So, the company made a strategic shift – investing heavily in the software and infrastructure needed to harness its GPUs for AI workloads.

As you can imagine, that decision changed everything.

Today, Nvidia is the largest company in the stock market, boasting a valuation of over $4.3 trillion.

The lesson isn’t that AI is important.

It’s that the biggest fortunes often require a strategic shift.

Video games are still a big market, and Nvidia was likely tempted to keep its focus on what made it successful.

Instead, they decided that far greater opportunities were available by shifting their focus away from the past.

The Real Money in Technology Revolutions

When the automobile industry accelerated in the first half of the 20^th century, the early excitement centered on carmakers. In 1903, there were more than 250 of them.

But the companies supplying the essential components – steel producers, tire manufacturers, and oil refiners – often made the biggest fortunes.

The same thing happened during the dot-com boom.

Consumers flocked to websites and software platforms. But behind the scenes, a massive infrastructure buildout was taking place – fiber-optic cables, semiconductor fabrication plants, networking equipment, and data centers.

That buildout created the Internet we know today.

AI is following the same pattern.

Mainstream media headlines focus on chatbots, image generators, and consumer applications. But the real story, and the opportunity, may be happening several layers deeper.

Training advanced AI systems requires staggering amounts of computing power. That means more GPUs… more data centers… more electricity… faster networks… and increasingly sophisticated communications technologies to move enormous amounts of information between machines.

In other words, the AI revolution is far more sprawling than what you’re reading about in The Wall Street Journal or seeing on CNBC.

It’s about building the infrastructure that will power the next generation of computing.

How to Play the AI Infrastructure Shift Today

Louis Navellier has spent decades studying these kinds of turning points and helping his readers position themselves appropriately so they can grow their wealth.

Louis has been analyzing markets since the early 1980s. Over that time, he’s built a reputation as one of Wall Street’s leading quantitative investors – using data-driven models to identify companies with the strongest earnings growth, sales momentum, and institutional buying.

His approach has helped him spot numerous major trends long before they became front-page news.

Regular Digest readers probably remember that Louis recommended Nvidia to his readers back in 2005 – long before the company became the dominant force in artificial intelligence computing.

Over the course of his career, he’s identified hundreds of stocks that went on to become major winners, including dozens of 1,000%+ winners

The New York Times, Forbes and Barron’s have all highlighted his work, describing him as an “icon among growth investors” and “one of the most successful fund managers in the country.”

Today, Louis’ system is telling him that we’re entering a new stage of the AI revolution – one where the biggest opportunities may lie not in the consumer applications grabbing headlines, but in the companies quietly supplying the infrastructure behind them.

Who Is Powering the AI Revolution

One of the biggest constraints on artificial intelligence today isn’t software.

It’s electricity.

Training advanced AI systems requires enormous computing power that consumes vast amounts of energy. Modern data centers already use staggering amounts of electricity, and the next generation of AI systems will demand even more.

That’s creating a new bottleneck and a new opportunity.

Louis believes one company positioned to benefit from this shift is Bloom Energy (BE).

Bloom’s roots go back decades. One of the company’s early pioneers helped develop hydrogen fuel cell technology for NASA’s Gemini space program in the 1960s.

Today, Bloom’s systems can convert fuels such as hydrogen, biogas, and natural gas into electricity, providing reliable on-site power for large facilities.

That reliability has made Bloom a popular solution for major corporations, including companies like Google (GOOG), Intel (INTC), FedEx (FDX), Walmart (WMT), Verizon (VZ, and AT&T (T).

But one of the fastest-growing uses for Bloom’s technology is now AI data centers.

Reliable power is critical for these facilities because AI workloads run around the clock and require a stable power supply to support thousands of high-performance processors.

Recently, the company expanded a major partnership with data center operator Equinix (EQIX), providing more than 100 megawatts of power capacity across 19 facilities.

Bloom has also announced that its fuel cells will help power Oracle Cloud Infrastructure data centers – another major AI computing hub.

And as AI infrastructure continues to expand, the demand for reliable on-site power is likely to grow right alongside it.

Since Louis’ recommendation in September, the stock has risen more than 120%.

AI might be powered by algorithms … but first it needs electricity.

BE is still trading well below Louis’ buy below price, so there is still room for this stock to run.

If you’d like to see how Louis is positioning his subscribers for this next phase of the AI revolution, including the companies he believes could benefit most from the massive infrastructure buildout now underway, you can learn more about his latest research here.

Louis has spent more than four decades studying market shifts and identifying companies with the strongest growth characteristics using his quantitative Stock Grader system.

In his latest free presentation, he explains why the AI boom may be entering a new stage and highlights several companies he believes are well-positioned to benefit.

You can read more about that research here.

Are You Positioned for the ÃÛÌÒ´«Ã½’s Strategic Shift?

Nvidia became the most valuable company in the market because it recognized that the chips designed to power lifelike explosions in games could also power the next generation of computing.

That single strategic shift helped turn a niche graphics company into the backbone of the AI revolution.

If history has taught investors anything, it’s that the companies quietly enabling a technological revolution often turn out to be some of the biggest winners.

Enjoy your weekend,

Luis Hernandez

Editor-in-Chief, InvestorPlace

The post The AI Boom’s Dirty Secret appeared first on InvestorPlace.

Complexity loses its premium, and adoption explodes. Profit pools shift. And that’s when money flows toward simplicity.

AI is bringing simplicity online in a big way. It’s what I like to call AI’s “Wallpaper” Phase.

You see, investors love the wiring phase: chip demand, GPU orders, data center build-outs, billions in capex.

But users don’t care how AI is wired. They care about convenience. Businesses care about productivity. ÃÛÌÒ´«Ã½s care about margins.

That intersection is where durability lives. And that’s where the next big opportunity to gain exposure to the AI wave is taking shape.

AI’s Everything Plug: Model Context Protocol

MCP—Model Context Protocol—is the underlying layer that connects AI to websites across the internet.

And I want to make one thing very clear. The only stocks that will thrive during AI’s next phase are the ones that go all-in on MCPs. The evidence is right in front of us.

AI assistants—ChatGPT, Claude, and others—are becoming the way people shop and interact online.

They need to connect to real businesses to work—stores, banks, software platforms. MCP is the new universal connection layer that allows AI assistants to do exactly that.

Google. Microsoft. Amazon. OpenAI. They’re all adopting it. And the emerging use cases for MCP tell us why.

Just imagine this:

You tell your AI assistant, “Find me a blue cashmere sweater under $200, size large, and buy it.”

The AI searches thousands of stores—but only those connected via MCP.

It selects three options. Your saved payment method is used. The item shows up at your door.

No website visited. No app opened. Not even a Google search. Just a seamless experience that users barely notice.

Growing Opportunity: New Wave. New Winners.

I’m using this example to make one point extremely clear.

If a company isn’t connected to AI infrastructure, it won’t even be in the conversation.

This is bigger than crypto. I haven’t felt this strongly about a technology since 2019. That’s back when I started talking about Ethereum early and positioned accordingly.

By 2030, this market could exceed $385 billion—larger than the entire U.S. online grocery market today.

Not all of the major players in AI will be winners. But the ones that will survive – and thrive – should certainly be on your radar.

With all that said, the AI boom is a magnet for volatility. The last few months alone have been marked by sector-wide market shocks that are seriously weighing down AI stocks.

And while my thesis hasn’t shifted, the next wave of profits in AI will come to those who manage their risk early – and understand the true stalwarts of the next AI infrastructure phase.

The Tech Sell-Off Isn’t What You Think

Tech stocks are having their “Black Monday” moment right now.

Major software companies from Salesforce (CRM) to Adobe (ADBE) have registered deep losses over the last few weeks. Why?

It all comes down to fears around AI and the future of work.

The market is pricing in a scenario where artificial intelligence could replace 50% or more of software roles.

Now consider that over 80% of major software stocks are owned by institutional investors (pension funds, index funds, hedge funds). The selloff happened because they always move in herds.

So when a company reports disappointing earnings or negative sentiment hits the sector, institutional investors who are overweight tech are essentially forced to dump positions. That creates massive selling pressure – regardless of long-term fundamentals.

All this indiscriminate volatility in tech looks familiar. It really suggests another quick, DeepSeek-like selloff. And just like we saw with that sell-off last year, markets recovered quickly despite fears around AI dominance.

The Logic is Simple

The players I mentioned above are so deeply embedded in enterprise infrastructure that they’re “too big to ignore.” Institutions absolutely must own them regardless of short-term AI concerns.

After the initial panic subsides, the same institutions that sold must eventually buy back in to maintain their sector allocations. And that creates predictable buying pressure we can act on right now.

These panic selloffs typically create 10-15% single-day discounts in otherwise healthy companies.

That’s exactly where we swoop in.

We’ve leveraged these pricing gaps with previous winners like C3.ai and even bearish plays on stocks like Asana that likely won’t survive AI’s next wave.

Each one trades on the same basic strategy.

This isn’t about believing AI won’t disrupt software—it’s about exploiting the gap between long-term uncertainty and short-term institutional behavior patterns that create predictable price movements. That volatility is where we live.

And just like last year’s panic selling, volatility is handing us serious opportunities – if we look in the right corners of the stock market.

I’d like to show you a better way to trade on every volatile market swing with The Masters in Trading Challenge.

It’s a seven-day intensive designed to show you how to take everything you’ve learned in my daily LIVEs — fixed risk, thesis-driven exits, laddered entries, defined-duration trades, and emotional discipline — and put it into practice in a structured, step-by-step environment.

Just click here to learn more about the Challenge.

Now, let me show you where I’m finding the strongest signals around AI right now…

IGV: The “Everything AI” ETF Play

The iShares Expanded Tech-Software Sector ETF (IGV) is a basket of roughly 100 software companies — and it’s widely used by institutions and retail investors for broad exposure to the AI boom.

IGV has been falling as all these SaaS names get absolutely crushed. The ETF is down sharply in 2026. Roughly a trillion dollars in market cap has been wiped from the space.

SaaS names like CrowdStrike are double digits And many more are still in free fall.

But here’s the problem with ETF selling…

When investors panic and sell the ETF, market makers must liquidate the entire basket.

It doesn’t matter if the company is fundamentally strong or on a shaky foundation. Like I mentioned above, herd mentality always drives institutions to sell.

That means quality stocks always get punished alongside companies that truly deserve it.

But this recent panic is even more overblown than the headlines suggest.

Since late February, IGV has been holding above $80. That’s a key level for us – our new “Line in the Sand.” Any slight dips could mean another pullback from here – but I’m fundamentally bullish on AI in the long-term.

We just need to find the AI survivors not only enduring this next wave – they’re building it all as I write to you.

3 AI Stocks Wall Street Isn’t Watching

Not all tech companies are equal in the AI world.

Some businesses like Asana and Docusign are directly threatened by AI automation. If AI can replicate the function cheaply and instantly, those names are vulnerable.

But other giants in the space – Microsoft, Apple, Google, to name a few – stand to benefit massively.

Now, those companies represent the top layer of the AI build-out. They’re building data centers, spending billions on software, and generally guiding the industry forward.

But for every big name like Microsoft, there are a handful of players positioned for the same shift that fly way under the radar.

Make no mistake – they’re just as big and important as the headline stocks I highlighted above. I recently went live to discuss three of these names  with the Masters in Trading community. And I’ve only gotten more bullish on these stocks since then.

1. Shopify (SHOP)

Shopify has been beaten down because investors are treating it like a traditional SaaS company. But it’s not.

Shopify is deeply embedded in AI commerce infrastructure. It partnered with Google to help build the standard language AI agents use for shopping. Walmart, Target, Visa, and Mastercard have all signed on.

Revenue is $11.6 billion—and growing. Shopify is set to become one of the most essential payment rails for AI-driven commerce.

2. Cloudflare (NET)

Cloudflare has been dragged down with SaaS names. But Cloudflare is hosting the AI servers that facilitate our access to software.

If Shopify is the payment rail, Cloudflare is the infrastructure backbone. It is critical to how AI agents connect and operate.

3. Twilio (TWLO)

Twilio plays a crucial role in AI communication. It’s how AI agents communicate—messaging, verification, transactional interaction.

The AI Trader’s Playbook

AI is making the services these companies provide even more indispensable.

That’s the transition I’m focused on right now.

Not speculative moonshots. Not headline AI hype.

Just large-scale distribution platforms where AI gets layered onto recurring revenue streams and seamlessly serves millions of users.

Here’s what traders need to know right now…

You don’t need to be the builder. Follow the money, not the headlines.

Watch hedge funds, and endowments. Watch insider buying and selling. Look for margin expansion.

And don’t chase flashy AI startups. Many winners will be boring. But this is all about allocation, not speculation.

If you’re interested in learning more about the opportunities I’m tracking in this space…

The Masters in Trading Options Challenge is right here to help you in your journey.

The Challenge is where we take everything you’ve learned in my daily LIVEs — fixed risk, thesis-driven exits, laddered entries, defined-duration trades, and emotional discipline — and put it into practice in a structured, step-by-step environment.

Just click here to check out what the Masters in Trading Options Challenge has in store for you.

Remember, the creative trader wins.

The post AI’s ‘Wallpaper’ Phase Is Here — Tech’s Next 3 Winning Stocks Revealed appeared first on InvestorPlace.

Algorithms now account for a large share of daily trading, and major headlines can move markets in seconds. That can make stocks feel more volatile than they used to.

In this kind of market, simply buying a great company and waiting can still work. But it often requires patience and the ability to ride through big swings. Case in point, I have often called some good, smaller stocks “bunny stocks” – because they tend to sit for a while and then “hop” around earnings season or when a major catalyst happens.

My friend and colleague Luke Lango focuses on finding those moments when stocks “hop” and pick up momentum.

In the essay below, he explains why volatility has become part of today’s market and how a breakout strategy can help investors take advantage of it.

Luke recently shared this approach in a free presentation. In backtesting, the same framework identified stocks that delivered gains of 2,623%, 865% and 2,149%. He also says the system has recently flagged four stocks that could be setting up for a similar move – and he reveals one of them during the broadcast.

You can watch the full presentation here.

Here’s Luke with more…

***

On Saturday, at roughly 9 a.m. in Tehran, explosions lit up the Iranian capital.

Wall Street didn’t wait for the morning shows. It didn’t wait for analysis. It didn’t even wait for traders to wake up.

Within milliseconds, trading algorithms had already processed the headlines, recalculated risk, and started selling.

By the time most of us saw “U.S.-Israel strikes Iran” on our phones, equity futures were sharply lower, oil was spiking, and volatility was jumping.

No panic on a trading floor. No shouting brokers.

Just machines.

This is how markets work now. Wars don’t slowly ripple through investor psychology anymore. They hit the wires — and algorithms pull the trigger.

More than 70% of U.S. equity trades are now executed by algorithms (and in certain high-frequency windows, that figure approaches 90%).

At the same time, retail participation has surged, with brokerage cash flows jumping more than 50% last year.

Fast machines. Record individual participation.

That combination creates a market that feels jumpier than ever.

I hear it from readers all the time: “I’m doing everything right… and it still feels like I’m one bad afternoon away from losing months of progress.”

That anxiety is real — and rising.

Just look at the extremes:

• Netflix Inc. (NFLX) down 75% in six months…
• Bill Ackman reportedly losing $400 million on that trade in three months…
• And a profitless “meme” stock like Opendoor Technologies Inc. (OPEN) rallying 900% while stronger peers finished the year down.

No wonder investors feel on edge.

So what’s the answer?

Not prediction. Not panic.

A process.

Treat volatility as information, and then focus on the one signal that tends to survive chaos: breakouts.

The opportunity isn’t in reacting to headlines. It’s in recognizing when a stock quietly shifts from consolidation into momentum, before the crowd shows up.

That’s what we’ll walk through next…

Chaos Is an Asset Class… If You Have the Right Map

Volatility doesn’t care about your retirement timeline.

It doesn’t care how “strong” the fundamentals look on paper.

When missiles strike while we sleep, the algorithms start firing before most investors have poured their first cup of coffee.

And just like that, months of steady gains can evaporate in an afternoon.

If your strategy depends on markets moving calmly and gradually, you have a problem.

Yet momentum traders are having their best stretch in years. Study after study shows momentum strategies tend to outperform over time.

The reason is simple.

You’re not predicting the future.

You’re reading the present.

But spotting genuine momentum before it becomes obvious requires more than instinct. It requires a system.

Introducing Stage Analysis: The Hidden Architecture of Every Stock

In 1988, trading pioneer Stan Weinstein outlined a framework in his book, Secrets for Profiting in Bull and Bear ÃÛÌÒ´«Ã½s, that changes how you see stock charts.

His thesis: Every asset moves through four stages.

• Stage 1: Sideways consolidation, largely ignored.
• Stage 2: Breakout and sustained advance.
• Stage 3: Distribution, as smart money exits.
• Stage 4: Decline.

The money is made in Stage 2.

Consider a few examples…

Palantir Technologies Inc. (PLTR) entered Stage 2 in May 2023 around $9. By late 2025, it traded above $200.

Carvana Co. (CVNA) broke into Stage 2 at nearly $7 in May 2023. It climbed more than 6,500%.

The investors who caught those moves didn’t need insider information. They recognized the Stage 2 setups before the rest of the market showed up.

That’s the power of stage analysis.

A System That Does the Work for You

Identifying true Stage 2 breakouts across thousands of stocks before they move requires serious analytical horsepower.

That’s why my team and I have built a system that quantifies Weinstein’s framework into a proprietary scoring model – grading thousands of stocks in the market from 0 to 5 based on the strength of their momentum setup.

In back-testing, it flagged eight of 2025’s top-performing stocks before their big runs, including:

• Hycroft Mining Holding Corp. (HYMC) before a 1,100% move.
• Terns Pharmaceuticals Inc. (TERN) before an 865% surge.
• MP Materials Corp. (MP) months before the Pentagon deal and a partnership with Apple Inc. (AAPL) sent it to the moon.

The system doesn’t chase headlines.

It looks for one thing.

Stocks on the verge of entering Stage 2.

In a market driven by algorithms and geopolitical shocks, reading price structure instead of predicting headlines isn’t optional.

It’s essential.

The Window Is Open, but It Won’t Stay That Way

AI has fueled a powerful bull market. But history shows late-stage rallies can accelerate – and then reverse just as quickly.

That doesn’t mean you sit on the sidelines.

It means you use the right tools while the opportunity is still there.

Volatility isn’t going away.

Geopolitical shocks aren’t going away.

Algorithms aren’t going away.

But chaos always produces outliers – stocks entering stealth bull markets while the rest of the headlines scream crisis.

The question is whether you have a way to find them.

In my latest free presentation, I explain why the old playbook no longer works… and what’s replacing it.

You’ll see how volatility has become the new normal… why buy-and-hold now feels like a white-knuckle ride… and how my Stage 2 breakout strategy is designed to target stocks just as major momentum runs begin.

I’ll walk you through the four-stage framework, show you how my upgraded Nexus Stock Screener analyzes more than 3,000 stocks in seconds, and reveal the name and ticker of a stock the system just flagged.

If you’re tired of reacting to market chaos, and ready to get ahead of the next major move, this broadcast is for you.

Click here to watch it now.

Sincerely,

Luke Lango

Editor, Hypergrowth Investing

The post When Algorithms Control the ÃÛÌÒ´«Ã½, Patience Isn’t Enough appeared first on InvestorPlace.

Models got smarter. Hallucinations declined. Context windows expanded. Coding ability improved.

But in 2026, something different is happening.

The curve is bending upward.

Look at the benchmark data highlighted during Google’s recent Gemini 3.1 Pro launch, and you’ll see scores that would have been considered science fiction just 18 months ago:

• 94.3% in scientific knowledge testing
• 77.1% in abstract reasoning puzzles specifically designed to be hard for AI
• 85.9% in agentic search
• 84.9% in long context performance
• And in expert task evaluation, Claude Sonnet 4.6 is sitting at 1633, leading the pack here entirely.

When leading labs are posting major benchmark scores that would have represented the outer limit of credibility in 2025, you’re no longer looking at marketing. You’re looking at a trend.

Right now, the METR time-horizon data may be the most important chart in technology. It measures something far more concrete than benchmark scores: how long an autonomous AI agent can sustain productive work on real engineering tasks.

And that line has gone nearly vertical. 

From minutes to hours in roughly three years. From two hours to 14 hours in just 12 months. 

If we follow that curve, we arrive at something that looks like full-day, then full-week autonomous operation within a year or two.

In other words, the Great AI Acceleration has begun…

Which means the economy may soon face a stress test so severe, it makes the shocks of 2008 look modest in comparison.

Why AI Leaders Are Suddenly Talking About AGI

The most telling signal isn’t public benchmarks. It’s how the insiders are talking.

Frontier AI leaders Sam Altman, Dario Amodei, and Demis Hassabis have all recently suggested that artificial general intelligence may be closer than the consensus believes.

In simple terms, AGI refers to AI systems capable of performing most knowledge-based tasks at or above the level of a typical human professional – autonomously and at scale.

These are people with access to internal capability evaluations that the public never sees, who have fiduciary duties to their investors, and who have spent years carefully managing expectations. 

The obvious counterargument is that they have every incentive to hype their own products. 

That’s fair. But consider what they’d actually gain from exaggerating timelines right now: regulatory scrutiny, congressional hearings, spooked employees, and a credibility problem when the timeline slips. 

The risk-reward on dishonest AGI boosterism is not great. So, when insiders sound alarmed, we should take that seriously, not dismiss it.

Follow the $710 Billion In AI Infrastructure Spending

But even if we feel like we can’t trust the words, we can follow the money – because cash doesn’t lie.

Combined hyperscaler capital expenditure for 2026 is now tracking toward $710 billion. That is not speculative enthusiasm. That is Microsoft (MSFT), Alphabet (GOOGL), Amazon (AMZN), Meta (META), and Oracle (ORCL) making multi-year, balance-sheet-altering commitments to build the infrastructure for something they clearly believe is coming. 

These companies have CFOs and boards and shareholder accountability. They don’t write $710 billion checks on vibes.

Layer on top of that Anthropic closing in on a $30 billion raise and OpenAI raising capital at valuations approaching $100 billion. The venture community is making directional bets with real money at a scale that implies genuine conviction about near-term transformative capability. 

CEOs can posture. Venture capital can exaggerate.

But $710 billion in hyperscaler capex is not theater. It’s preparation.

And the market is beginning to understand that.

What the Stock ÃÛÌÒ´«Ã½ Is Saying About AI

The IGV software ETF is down 24% year-to-date – one of its steepest drawdowns since the 2008 financial crisis. Meanwhile, the broader market is essentially flat.

A 24-point divergence between a sector and the market is a verdict. 

The market is concluding that traditional software businesses – the enterprise Software-as-a-Service (SaaS) stack that has powered a generation of wealth creation – are facing an existential question about their reason to exist.

If AI models become genuinely capable of performing most knowledge work tasks autonomously – as the current trajectory suggests – then the question isn’t whether software stocks are oversold. The question is which software companies are building the picks and shovels for the AI era – and which are selling products that AI will simply replace.

That is not a subtle distinction. And it’s exactly why the market is reallocating.

But how soon does ‘replacement’ become reality?

The AI Acceleration Timeline: How Close Is AGI?

The METR data suggests we may not be far away from achieving AGI. 

It is the kind of timeline that feels simultaneously urgent and abstract, which is precisely why most people will not take it seriously until it is too late.

If AI reaches AGI-level capability within two years, the economic consequences bifurcate sharply along a single axis: do you own AI capital, or do you sell labor that AI can replicate?

For those on the capital side of that line, the profit potential is extraordinary. AI doesn’t work for pay or take sick days. It scales instantly and degrades gracefully. A company that swaps AI for knowledge workers rewrites its margin structure. Payroll becomes compute. Compute scales, and margins expand. For shareholders in true AI-native businesses, that’s the holy grail: growth and operating leverage at the same time.

For those on the labor side, the contrast is stark and much more grim. Previous automation waves displaced physical workers over decades – long enough for retraining, for new industries to emerge, and for society to absorb the shock. But this AI wave is targeting knowledge workers, who have historically been the beneficiaries of automation rather than its victims; and it is moving on a timeline measured in years rather than generations. The social safety nets, retraining programs, and political institutions that might buffer that displacement were not designed for this scenario.

The result, if left unaddressed, is a society stratified not by education or skill but by proximity to AI capital: a techno-feudal order, if you will, in which the owners of the models are the lords, and everyone whose labor the models can replicate are the serfs. 

It is not a pretty picture. 

And while it is also not an inevitable one – since policy, redistribution, and political will can alter this trajectory – the window to shape that outcome may be narrower than most realize… and closing fast.

How Investors Are Positioning for the AI Economy

The investment implication here writes itself: if AI is the new engine of wealth, you want to own the engine.

Own the model builders, the infrastructure providers, the companies that are genuinely AI-native rather than merely AI-adjacent.

This is the obvious trade for a reason; but there are also a few caveats to keep in mind.

The Bottom Line

The Great AI Acceleration is upon us. 

The question is not whether AI will be transformative. The question is how fast, how concentrated, and how prepared any of us are for what comes next.

The METR chart is the most important chart in the world right now. A line that started near zero and has gone nearly vertical is, historically speaking, the kind of line that does not stop on its own.

We are, in all probability, in the early stages of something that will make the internet revolution look like a warm-up act. 

The techno-lords are assembling their estates. If you don’t want to be collateral damage, be very careful where you park your capital.

And right now, the most important estate in AI isn’t public. It’s OpenAI.

Reports suggest a 2026 IPO is coming. And when OpenAI goes public, it could be the most anticipated IPO since Facebook – and potentially the first trillion-dollar AI debut.

History is clear: the biggest gains don’t go to the investors who buy on IPO day. They go to the ones who positioned themselves before the public even gets access.

I’ve identified a little-known way to do exactly that – for under $10.

If you’re going to pick a side in the AI revolution, this is the one event you can’t afford to ignore.

The post The AI Acceleration Curve Just Went Vertical appeared first on InvestorPlace.

In today’s Friday Digest takeover, our hypergrowth expert Luke Lango explains why modern markets behave differently than they did even a decade ago. With algorithms executing the majority of trades and geopolitical headlines hitting the tape at all hours, prices can shift before most investors have time to react.

The result is a market that feels unpredictable – unless you know where to look.

Luke argues the key isn’t trying to forecast every headline, but identifying when a stock quietly shifts from consolidation into momentum – what traders call a Stage 2 breakout – before the crowd catches on.

Below, Luke walks through how this framework works and why it has helped flag some of the market’s biggest winners over the last few years before their major runs.

And for a deeper dive, he’s put together a free presentation explaining how his upgraded system scans thousands of stocks to find these setups – and he reveals one name the system just flagged. You can watch that broadcast right here.

If you’ve been feeling the market’s whiplash lately, today’s Digest takeover is for you. I’ll let Luke take it from here.

Have a good evening,

Jeff Remsburg

On Saturday, at roughly 9 a.m. in Tehran, explosions lit up the Iranian capital.

Wall Street didn’t wait for the morning shows. It didn’t wait for analysis. It didn’t even wait for traders to wake up.

Within milliseconds, trading algorithms had already processed the headlines, recalculated risk, and started selling.

By the time most of us saw “U.S.-Israel strikes Iran” on our phones, equity futures were sharply lower, oil was spiking, and volatility was jumping.

No panic on a trading floor. No shouting brokers.

Just machines.

This is how markets work now. Wars don’t slowly ripple through investor psychology anymore. They hit the wires — and algorithms pull the trigger.

More than 70% of U.S. equity trades are now executed by algorithms (and in certain high-frequency windows, that figure approaches 90%).

At the same time, retail participation has surged, with brokerage cash flows jumping more than 50% last year.

Fast machines. Record individual participation.

That combination creates a market that feels jumpier than ever.

I hear it from readers all the time: “I’m doing everything right… and it still feels like I’m one bad afternoon away from losing months of progress.”

That anxiety is real — and rising.

Just look at the extremes:

• Netflix Inc. (NFLX) down 75% in six months…
• Bill Ackman reportedly losing $400 million on that trade in three months…
• And a profitless “meme” stock like Opendoor Technologies Inc. (OPEN) rallying 900% while stronger peers finished the year down.

No wonder investors feel on edge.

So what’s the answer?

Not prediction. Not panic.

A process.

Treat volatility as information, and then focus on the one signal that tends to survive chaos: breakouts.

The opportunity isn’t in reacting to headlines. It’s in recognizing when a stock quietly shifts from consolidation into momentum, before the crowd shows up.

That’s what we’ll walk through next…

Chaos Is an Asset Class… If You Have the Right Map

Volatility doesn’t care about your retirement timeline.

It doesn’t care how “strong” the fundamentals look on paper.

When missiles strike while we sleep, the algorithms start firing before most investors have poured their first cup of coffee.

And just like that, months of steady gains can evaporate in an afternoon.

If your strategy depends on markets moving calmly and gradually, you have a problem.

Yet momentum traders are having their best stretch in years. Study after study shows momentum strategies tend to outperform over time.

The reason is simple.

You’re not predicting the future.

You’re reading the present.

But spotting genuine momentum before it becomes obvious requires more than instinct. It requires a system

Introducing Stage Analysis: The Hidden Architecture of Every Stock

In 1988, trading pioneer Stan Weinstein outlined a framework in his book, Secrets for Profiting in Bull and Bear ÃÛÌÒ´«Ã½s, that changes how you see stock charts.

His thesis: Every asset moves through four stages.

• Stage 1: Sideways consolidation, largely ignored.
• Stage 2: Breakout and sustained advance.
• Stage 3: Distribution, as smart money exits.
• Stage 4: Decline.

The money is made in Stage 2.

Consider a few examples…

Palantir Technologies Inc. (PLTR) entered Stage 2 in May 2023 around $9. By late 2025, it traded above $200.

Carvana Co. (CVNA) broke into Stage 2 at nearly $7 in May 2023. It climbed more than 6,500%.

The investors who caught those moves didn’t need insider information. They recognized the Stage 2 setups before the rest of the market showed up.

That’s the power of stage analysis.

A System That Does the Work for You

Identifying true Stage 2 breakouts across thousands of stocks before they move requires serious analytical horsepower.

That’s why my team and I have built a system that quantifies Weinstein’s framework into a proprietary scoring model – grading thousands of stocks in the market from 0 to 5 based on the strength of their momentum setup.

In back-testing, it flagged eight of 2025’s top-performing stocks before their big runs, including:

• Hycroft Mining Holding Corp. (HYMC)before a 1,100% move.
• Terns Pharmaceuticals Inc. (TERN) before an 865% surge.
• MP Materials Corp. (MP) months before the Pentagon deal and a partnership with Apple Inc. (AAPL) sent it to the moon.

The system doesn’t chase headlines.

It looks for one thing.

Stocks on the verge of entering Stage 2.

In a market driven by algorithms and geopolitical shocks, reading price structure instead of predicting headlines isn’t optional.

It’s essential.

The Window Is Open, but It Won’t Stay That Way

AI has fueled a powerful bull market. But history shows late-stage rallies can accelerate – and then reverse just as quickly.

That doesn’t mean you sit on the sidelines.

It means you use the right tools while the opportunity is still there.

Volatility isn’t going away.

Geopolitical shocks aren’t going away.

Algorithms aren’t going away.

But chaos always produces outliers – stocks entering stealth bull markets while the rest of the headlines scream crisis.

The question is whether you have a way to find them.

In my latest free presentation, I explain why the old playbook no longer works… and what’s replacing it.

You’ll see how volatility has become the new normal… why buy-and-hold now feels like a white-knuckle ride… and how my Stage 2 breakout strategy is designed to target stocks just as major momentum runs begin.

I’ll walk you through the four-stage framework, show you how my upgraded Nexus Stock Screener analyzes more than 3,000 stocks in seconds, and reveal the name and ticker of a stock the system just flagged.

If you’re tired of reacting to market chaos, and ready to get ahead of the next major move, this broadcast is for you.

Click here to watch it now.

Sincerely,

Luke Lango

The post Volatility Is the New Normal. Breakouts Are the Edge. appeared first on InvestorPlace.

In every market panic, investors face the same temptation: mistake motion for meaning.

A war headline hits. Oil jumps. Semiconductors wobble. Defense stocks catch a bid. Suddenly, every red candle feels like a warning and every green candle looks like a trade. But most investors do the most damage to their portfolios in moments like this not because they miss the news, but because they overreact to it.

That is the real challenge right now.

The market is trying to price an unstable mix of geopolitics, AI infrastructure demand, labor disruption, and shifting sector leadership all at once. On the surface, that creates chaos. Underneath it, though, a much more useful question is emerging: which narratives are truly changing, and which ones are merely being tested?

Because while traders fixate on Iran, oil routes, and daily volatility, the bigger investment story has not disappeared. It has simply become easier to miss. The AI buildout is still the dominant growth engine in this market, but this week exposed a pressure point many investors had not fully appreciated…

South Korea’s role in the global memory supply chain.

If that chokepoint tightens, the ripple effects won’t stop with Samsung and SK Hynix. They can run through Micron (MU), SanDisk (SNDK), Western Digital (WDC), Seagate (STX), Nvidia (NVDA), and the broader semiconductor complex.

At the same time, another shift is becoming harder to ignore. Block’s sweeping layoffs may prove to be more than an isolated corporate decision. They may be an early sign that AI is moving from productivity tool to workforce replacement mechanism faster than investors expected. That has major implications not just for software and fintech, but for margins, hiring, and the broader economy.

Meanwhile, defense remains a live theme, with names like AeroVironment (AVAV), Lockheed Martin (LMT), Northrop Grumman (NOC), RTX (RTX), L3Harris (LHX), and Teledyne (TDY) still positioned to benefit from a world spending more on security and less on wishful thinking.

So this week’s real opportunity is not about chasing the loudest headline. It is about identifying what deserves your attention, what does not, and where the next durable winners are likely to emerge before the market fully settles on the answer.

Check out our weekly podcast below:

The post The Iran Conflict Is Reshaping Every ÃÛÌÒ´«Ã½ Right Now appeared first on InvestorPlace.

I didn’t have a scholarship to a fancy Ivy League school or any insider Wall Street connections.

My father worked as a bricklayer for 40 years, starting his day at 5 a.m. and often not coming home until late in the evening.

I was the first person in my family to go to college. It wasn’t until one of my professors in graduate school gave me an assignment that would change the course of my life forever.

The assignment: Create a system that would mirror the S&P’s performance.

I was given access to powerful mainframe computers to do it.

Except there was one little problem.

My system beat the S&P.

It turns out that a select group of stocks shared certain characteristics that led them to consistently outperform the market.

And that is how Stock Grader (subscription required) was born. It uses a simple A-F grading system that assigns a Total Grade to thousands of stocks based on two crucial characteristics, which can make a huge difference in choosing a stock that delivers consistent gains.

So, in today’s ÃÛÌÒ´«Ã½ 360, I’ll share with you some key details on how Stock Grader works. I’ll also show you one of my top picks that I found using it. And to wrap up, I’ll explain how this straightforward framework can make investing clearer for everyday investors. (In fact, I even taught my daughter how to use it…)

Let’s get started.

Breaking It Down

There are two characteristics that determine a stock’s Total Grade: The Fundamental Grade and the Quantitative Grade.

Let’s look at the Fundamental Grade first.

There are eight specific factors I consider to gauge a stock’s Fundamental Grade…

1. Sales Growth: This is just as it sounds, and it’s the hardest number to fake. Great companies continually look for ways to increase their month-to-month and year-to-year sales so they can expand and deliver big returns to their shareholders.

2. Operating Margin Growth: The margin shows the difference between production costs and retail prices. The wider the difference, the better. We want to see a company that can expand its operating margins by raising prices (or cutting costs) without seeing a sales decline. On the flip side, if a company keeps reducing prices just to entice buyers, that’s not a good sign.

3. Earnings Growth: This determines whether a company has earned more money year-over-year. It is measured in earnings per share. It is the company’s earnings divided by the number of shares outstanding. I want to see continual, year-over-year growth.

4. Earnings Momentum: This tells me the rate of a company’s growth based on its earnings. If it’s going up, then you’ll likely see a bigger return on your investment.

5. Earnings Surprises: An earnings surprise is when a company beats analysts’ earnings estimates. It’s measured as a percentage and calculated as the difference between actual earnings and consensus estimates. If a company is consistently beating estimates, its share price can rise significantly.

6. Analyst Earnings Revisions: I like to see increasing analyst earnings estimates. Upward revisions are not taken lightly, and an analyst will only do it if they have strong confidence. It’s likely that the stock will outperform those expectations.

7. Cash Flow: This measures cash earned and spent relative to its market value. It shows how much money a company has left over after covering its business costs. The more cash they have, the better!

8. Return on Equity: This is what a company generates with the money shareholders have invested. It shows how efficiently a company manages its resources.

The Quantitative Grade measures the stock’s institutional buying pressure.

Buying pressure is a fancy way of saying where the “smart money” is flowing. This “smart money” comes from large institutional investors, such as investment banks, hedge funds or pension funds, who invest in the stock. The more “smart money” coming in, the more momentum the stock has to rise.

Stock Grader blends the Fundamental Grade and Quantitative Grade together and gives the stock a Total Grade of A-F:

• A=Very Strong
• B=Strong
• C=Neutral
• D=Weak
• F=Very Weak

Putting Stock Grader to the Test

Now let’s look at an example of Stock Grader at work in the real world.

One of the top-performing stocks in my Growth Investor service is Agnico Eagle Mines Ltd. (AEM), the second largest gold producer in the world.

I first recommended it in August 2024, when gold prices were rising due to escalating geopolitical conflict and a lack of confidence in central banks.

I knew gold prices were likely to continue rising. And since gold miners have the benefit of operating leverage, they can benefit tremendously from rising gold prices – often returning much more than the price of gold alone.

At the time, Agnico Eagle Mines had a Total Grade of A, which already signaled strong fundamentals and buying pressure. That grade signaled the kind of strength I look for when identifying potential market leaders.

Since I recommended it, my Growth Investor subscribers are now up nearly 180%.

The big question, though, is what does Stock Grader think of Agnico Eagle Mines now?

Let’s take a look…

It still earns a Total Grade of A, making it a Very Strong stock.

It also earns a Fundamental Grade of B and a Quantitative Grade of A, indicating that its fundamentals and buying pressure are still strong.

You can see the specific grades for each fundamental metric in the image below.

Based on these factors, I would consider Agnico Eagle Mines a very strong addition to any growth-oriented portfolio.

The Power of Stock Grader Is for Everyone…

The power of Stock Grader lies in its simplicity… and it’s allowed my followers the chance to make huge gains over the years.

Back in 1998, I recommended Cisco Systems Inc. (CSCO), which went up over 200%. Then, in 2004, I told readers to get in on América Móvil, S.A.B. de C.V. (AMX), which rose over 370% from there.

And more recently, in 2016, I recommended NVIDIA Corporation (NVDA). Today, those Growth Investor subscribers who got in on NVIDIA back then are now sitting at a gain of over 4,000%.

I could go on with a ton of examples like this, but you get the idea.

The point is, when I think back to those early days – growing up in a blue-collar household, watching my father leave before sunrise – I never imagined I’d one day build a system that anyone could use to navigate the markets.

But these days, I’m making it my mission to pass this on to every investor who’s willing to try it – including my 25-year-old daughter, Crystal, an art student with no financial background.

It’s not hard to pick up. In fact, I taught this to my daughter over a pizza dinner one night.

She went on to build a portfolio using Stock Grader that outperformed the broader market by nearly 2-to-1 last year.

That’s why I put together my latest briefing, to show you how Stock Grader works and how Crystal applied it, too.

I’ll also explain why your money is at risk with traditional index funds right now. In fact, in recent months, the situation has become so dire that I’ve warned Crystal never to put her money in an index fund. 

Plus, I’ll share the name and ticker of a top-rated company I believe has tremendous upside potential.

Click here to watch the full briefing now.

Sincerely,

Louis Navellier

Editor, ÃÛÌÒ´«Ã½ 360

The Editor hereby discloses that as of the date of this email, the Editor, directly or indirectly, owns the following securities that are the subject of the commentary, analysis, opinions, advice, or recommendations in, or which are otherwise mentioned in, the essay set forth below:

Agnico Eagle Mines Ltd. (AEM), Cisco Systems Inc. (CSCO) and NVIDIA Corporation (NVDA)

The post The System I Use to Beat the S&P 500 – And Now My Daughter Is,Too… appeared first on InvestorPlace.

Not the financial press, not the tech leaders; certainly not the politicians who are, in many cases, actively participating in it. 

Instead, the story is dressed up in the language of innovation, disruption, progress, and national competitiveness. It’s celebrated in earnings calls and keynote speeches, packaged as exciting news about a technology that will make all of our lives better.

And it might, eventually. Just not before it makes a small group of people generationally wealthier – while most others are stifled.

What is happening has a name. And if you don’t understand it, you are already falling behind.

A Historical Parallel Worth Revisiting

In England, between the 16th and 18th centuries, the landowning class executed one of the most consequential wealth transfers in history. They called it enclosure. 

The common lands that ordinary people had farmed and depended on for generations – the shared economic foundation of an agrarian society – were gradually privatized. Parliamentary acts were passed. Fences went up. Farmers and laborers who had worked the land for generations found themselves trespassing on what used to be theirs.

They didn’t disappear. They lost their independent economic footing and became dependent on the very people who had enclosed the land. And they became the labor force for the Industrial Revolution.

The enclosers didn’t think of themselves as villains. They were “rational actors” with good lawyers, political connections, and a compelling narrative about efficiency and progress. The fences, they argued, were actually better for everyone in the long run.

The pattern may sound familiar…

The ‘AI Enclosure’: How Artificial Intelligence Is Privatizing Cognitive Labor

The “AI Enclosure” is the 21st-century version of this same story – and it is happening right now, in real time, while most people are busy arguing over politics and worrying over their job security.

What is being enclosed this time is not land. It is intelligence itself.

For most of modern history, cognitive ability – the capacity to read, write, reason, analyze, build, create, persuade – has been a broadly distributed endowment. You cultivated it through education and experience. It was yours. No one could take it from you. In an economy built on knowledge work, that endowment was your ticket to the middle class; your identity and security.

A small number of companies are beginning to concentrate control over that endowment. 

They are encoding human intelligence into model weights, embedding it inside proprietary systems, and charging rent for access to a resource that used to belong to everyone who developed it. 

The senior product manager, the paralegal, the financial analyst, the mid-level software engineer – these people spent years and borrowed money building cognitive skills they were told would always be valuable.

The fences are going up around those skills. And the people raising them are not asking for permission.

The Moment the AI Labor Shift Became Obvious

Most major structural shifts have a watershed moment, when the abstract becomes undeniable – when the thesis stops being a prediction and becomes a description.

We think we just had ours.

Last week, Block (XYZ) CEO Jack Dorsey announced that the company – the fintech conglomerate behind Square, Cash App, and Afterpay – would cut 4,000 employees, roughly 40% of the entire workforce. It was the largest single-round percentage layoff in the history of the S&P 500.

He didn’t frame it as a cost-cutting measure, blame the economy or the market, or claim it was the result of a strategic pivot gone sideways. He said, plainly, that “intelligence tools have changed what it means to build and run a company” – and that he’d rather get there honestly and on his own terms than be forced into it reactively.

In effect, Dorsey didn’t just fire 4,000 people. He fired the starting gun. He gave every CFO at PayPal (PYPL), Shopify (SHOP), Stripe, Adyen (ADYEY), and every financial services firm watching nervously from the sidelines the thing they needed most: cover. The moment one player in a competitive industry achieves structurally lower operating costs through AI-driven headcount reduction, the others face a binary choice: match the efficiency, or compete at a permanent cost disadvantage.

In a low-margin industry, there are few alternatives – which means the pressure to follow suit will spread quickly. So, fintech will cut. Broader financial services will follow. Then software, consulting, law, accounting… The logic that justified Block’s announcement applies to every industry where the primary input is human cognitive labor – where people are paid, essentially, to think.

That is the knowledge economy, which employs tens of millions of Americans. And Dorsey just announced that its restructuring has begun.

The New Power Structure of the AI Economy

The AI Enclosure is not a hidden conspiracy. It is a publicly legible, mutually reinforcing network of capital, technology, and political power that has converged with unusual speed and clarity around a single asset class.

The Hyperscalers: Owners of AI Compute Infrastructure

Microsoft (MSFT), Alphabet (GOOGL), Amazon (AMZN), Meta (META). They own the compute infrastructure – the data centers, cloud platforms, and distribution channels through which AI reaches the economy.

The Model Builders: The Companies Controlling AI Intelligence

OpenAI, Anthropic, xAI, Google DeepMind. They own the AI itself – the model weights that encode humanity’s accumulated knowledge and make it available to whoever can pay for access.

The Semiconductor Gatekeepers of the AI Economy

Nvidia (NVDA), Taiwan Semiconductor (TSM), Broadcom (AVGO). They manufacture the physical hardware on which all of this runs. Nvidia’s GPUs function almost like the oil wells of the AI economy.

The Capital Network Funding the AI Boom

Andreessen Horowitz, Sequoia, Founders Fund, and their satellites. They fund the ecosystem, take equity early, and harvest the returns at scale.

Blackstone (BX), Apollo (APO), and KKR (KKR) are positioned to harvest the displacement, buying distressed assets as the businesses that can’t adapt fail and recycling capital into the infrastructure of the businesses that replace them.

The Political Shield Protecting the AI Enclosure

This club is not operating in opposition to political power. It has merged with it.

Vice President of the United States J.D. Vance – former Silicon Valley insider, Peter Thiel protégé, close friend of Palantir‘s (PLTR) Alex Karp – is the connection point. Indeed, his friend Karp has an explicit ideological framework for this merger. He calls it the Technological Republic: the idea that America’s national destiny is inseparable from technological supremacy and that the people building that technology should have an outsized role in shaping the country’s direction. 

This is largely the operating philosophy of the current administration.

The result: many policy tools that could slow or reshape the Enclosure or distribute its gains have been pre-labeled as a threat to American competitiveness. 

Compute taxes? Handing the lead to China. 

Automation dividends? Socialism. 

The fences going up have political protection from the highest levels of government.

The AI Version of Engels’ Pause

There is a name for the waiting period between when a great technological transformation begins and when society builds the institutions to manage it equitably. 

Economic historians call it Engels’ Pause after Friedrich Engels, who documented that during Britain’s Industrial Revolution, real wages stagnated for decades even as GDP soared. 

The industrial gains were real. They just didn’t reach workers until unions, factory laws, public education, and, eventually, the welfare state forced the redistribution.

That institutional scaffolding took 80 years, and supporters had to fight for it every inch of the way.

We are likely entering the AI version of Engels’ Pause. The legislation that would end it – something that routes the gains back to the displaced like automation dividends, compute taxes, or universal basic income – faces the most hostile political environment imaginable. 

The constituencies who would benefit are diffuse and disorganized. The constituencies who would oppose it are the most concentrated, wealthy, and politically connected groups in the modern economy. And they are currently inside the administration.

The pause will likely endure for the foreseeable future – which means for the majority of Americans, the next several years will be a slow, grinding transfer of wealth from those who sell labor to those who own AI capital. 

Not a crash. A quiet, relentless enclosure.

How Investors Can Position for the AI Infrastructure Boom

I won’t pretend this is an easy thing to face. I’d say the appropriate emotional response to the AI Enclosure is outrage. 

But the appropriate investment response is cold-eyed pragmatism…

Because investors cannot stop the Enclosure – but they can position themselves inside it.

The Enclosure is, at its core, a bet on physical scarcity in a world of digital abundance. As intelligence becomes far cheaper and more abundant, the things that are genuinely scarce – the energy to power AI, the chips to run it, the physical infrastructure to house it, the land and permits and grid connections to build it – become extraordinarily valuable. 

The semiconductor is the oil well. The data center is the refinery. And the utility is the pipeline. So:

Own the ‘Oil Wells’ of AI: Semiconductor Leaders

Nvidia, TSM, Broadcom – these companies don’t just benefit from the AI buildout. They are the foundational constraint. Nearly every major AI model ultimately depends on hardware they manufacture. That is a royalty on cognition itself.

Own the ‘Refineries’: Hyperscale Cloud Platforms

The hyperscalers – Microsoft, Amazon, Google, Meta – own the compute and the distribution. They are the Enclosure’s landlords. They will be extraordinarily wealthy in every plausible scenario because they are too deeply embedded in the infrastructure of both the technology and the economy to lose.

Own the ‘Pipelines’: Energy for Data Centers

Energy is the most underappreciated and underowned trade in this entire framework. Data centers require extraordinary and growing amounts of power. Nuclear energy, natural gas infrastructure, grid modernization, and power management hardware will be essential. Constellation Energy (CEG), Vistra (VST), Kinder Morgan (KMI), Eaton (ETN), Vertiv (VRT) – these companies are boring in name and extraordinary in structural position. The AI buildout will require enormous amounts of the infrastructure they provide. Their revenue is contracted, long-duration, and insulated from the application-layer volatility that will shake the ‘sexier’ names.

Own the Real Estate of the AI Economy

Equinix (EQIX) and Digital Realty (DLR) are the landlords of the internet’s physical infrastructure. They lease the space and connectivity that hyperscalers depend on. They have long-term contracted revenue, irreplaceable physical assets – moats that software alone cannot replicate.

Avoid the ‘Friction Economy’

Any company whose business model depends on human cognitive labor, information asymmetry, habitual intermediation, or the inefficiencies that AI eliminates will face structural pressure. That means traditional software-as-a-service (SaaS) without strong proprietary data advantages, financial intermediaries built on inertia, staffing companies, offshore IT services. These are the knowledge economy equivalents of the hand-loom weavers – good businesses in the wrong century.

That divide – between the infrastructure of AI and the businesses disrupted by it – will likely define the early economics of this transition.

The Gate Is Closing

None of this guarantees a dystopian outcome.

History suggests technological revolutions rarely unfold in straight lines. Institutions adapt. New industries eventually emerge. The gains from major innovations have historically spread far more broadly over time than they do in their earliest stages.

But that process takes years – sometimes decades.

In the meantime, the early phases of every technological shift tend to concentrate wealth around the infrastructure that makes the new system possible.

Railroads created steel fortunes before they created middle-class prosperity.

Electrification made utility barons wealthy before it transformed household living standards.

The internet made semiconductor and network companies enormously valuable before the broader digital economy matured.

Artificial intelligence appears to be following a similar pattern.

The chips, data centers, power systems, and physical networks enabling AI are not speculative ideas about the future. They are being built right now at enormous scale, backed by hundreds of billions of dollars in capital commitments from the largest technology companies in the world.

The Final Word

Investors do not need to predict every consequence of the AI revolution to understand where the early economic gravity lies.

They simply need to recognize where the infrastructure of the new system is forming – and who owns it.

Because in every technological revolution, the people who own the infrastructure tend to benefit long before the rest of society figures out how to adapt.

One company sits closer to the center of that infrastructure than almost any other: OpenAI.

The same organization that launched ChatGPT and ignited the modern AI race is widely expected to enter public markets – potentially becoming the first pure-play way for everyday investors to own a piece of the intelligence layer itself.

And when that moment arrives, the demand could be enormous.

But investors who wait for the IPO headlines may already be late to the opportunity.

That’s why I recently put together a detailed briefing explaining a little-known way investors may be able to position themselves before OpenAI ever rings the opening bell.

You can see the full breakdown here.

The post The Hidden Wealth Transfer Inside the AI Revolution appeared first on InvestorPlace.

In our August 26, 2024, Digest, we warned investors about the risks that AI posed to software giant Adobe (ADBE):

For some part of the foreseeable future, AI advancements should help Adobe make jaw-dropping products for its designer clients that we would expect to boost earnings.

But what happens when AI grows so advanced that we no longer need digital designers?

Instead, you’ll just tell an AI Digital Design Bot what you want.

Well, in that case, without a drastic pivot, Adobe’s entire business model goes “poof.”

If that Digest scared you out of ADBE, congratulations – you sidestepped a 52% “poof.”

Let’s jump to our technology expert Luke Lango for more on the recent carnage in the software sector:

The tech industry spent years telling a beautiful story about AI.

“AI will make everything faster and smarter and better, and the companies building it will be the most profitable in history.”

But there was a flip side to that pitch: If AI can do everything its champions claim, it can replace everything its customers currently pay for.

That flip side has arrived.

In recent days, I’ve highlighted Luke’s analysis explaining the best way to invest in this “flip side.”

In short, investors need to be wary of companies that offer only digital products, while considering companies that facilitate the physical layer of AI.

Back to Luke:

What separates the winners from the losers?

Physical versus digital; atoms versus bits.

The companies being demolished are pure-play digital – software, platforms, marketplaces, fintech apps.

The companies soaring are manufacturers, hardware producers, and energy providers.

For the first time in about 15 years, having a physical business is a competitive advantage rather than a drag on margins.

Now, at the end of today’s Digest, I’ll name-drop a handful of potential winners and losers that Luke just highlighted. But before we get there, let me do you one better…

Let’s walk through a market approach you can use today to navigate this AI “sifting machine” on your own. It will help you sidestep the next AI destruction…and help you uncover the next soaring trade.

In fact, circling back to Adobe, even if you missed our August 2024 Digest… even if you had no awareness of how destructive AI would be for software stocks… this simple-yet-highly-effective market approach could have helped you sidestep the worst of this stock collapse.

Let’s talk about how, then get into the best ways to apply it today.

Price is truth

AI is rewiring our global economy.

No one knows exactly where this takes us, much less which stocks will be 100% higher or 50% lower by this time next year.

Circling back to software, here’s Luke making this point:

When investors look at a high-multiple Software-as-a-Service (SaaS) company and ask, “will this business still be here in five years?”, the honest answer is increasingly:

I genuinely don’t know.

The way around this is to focus on what we do know – price.

At the end of the day, our best analysis is irrelevant if it contradicts the core axiom of the stock market…

Price is truth.

It doesn’t matter if your spreadsheets, research, and discounted cash flow models conclude that a $50 stock should climb to $100. If it falls to $27, that’s “truth.”

Traders who fight that truth lose. Traders who respect it – and swim with the current, whether they agree with it or not – grow their wealth.

How “stage analysis” finds the market’s truth

As I noted yesterday, every stock is always in one of four unique stages: 1) going sideways at a bottom, 2) going up, 3) going sideways at a top, or 4) going down.

Stage analysis is the process of determining which stage a stock is currently in, and then investing only when it’s on the cusp of entering, or already surging, in Stage 2.

This puts all the emphasis on price, which is the North Star variable that directly impacts your wealth.

Here’s Luke highlighting its preeminence:

The only thing that will make a difference to your portfolio is whether the stocks you own rise in value while you own them.

Let’s say you found a truly atrocious company hemorrhaging cash, with awful management, in a dying industry.

But what if its stock price had just broken out and, hypothetically, was on its way to doubling from $5 to $10? Would any of those negative characteristics matter to you?

If what you care about is your personal wealth, they shouldn’t. Why would they?

All that would matter is that the stock is doubling while you’re invested…

When it comes to wealth-building, the only thing that truly matters is whether the share price moves in the direction you want during the period you own the stock.

Let’s apply this to Adobe

Below, we look at ADBE since the fall of 2022.

Here’s how it looks with a stage-analysis overlay.

Even if you missed our August 2024 Adobe call, following a stage analysis framework would have led you to sell the stock about four months later – around $445 – when ADBE fell below the support line of its Stage-3 topping pattern.

Adobe shareholders would have avoided a nearly 40% collapse to current prices.

How to play offense with stage analysis

This framework isn’t just about playing defense – its primary benefit is as an offensive weapon.

Below, we look at one of the hottest stocks of the last year, drone maker Kratos Defense & Security Solutions (KTOS).

Stage analysis led Luke to recommend KTOS in May 2023 – very early in its Stage-2 breakout…

Luke and his subscribers are still in this position, currently up 455% as I write.

Now, let me point out one important aspect of this trade…

Back in May 2023, when Luke recommended this drone maker, he had no way of knowing that the drone sector would soar as it has in recent years…or that the Russian/Ukraine war would still be relying heavily on drones today…or that they’d be used extensively in our current conflict with Iran…

In fact, forward-looking fundamental and macro analysis played no role whatsoever in Luke’s recommendation.

He simply followed price and volume through this stage analysis framework – that’s it.

Price is truth.

Applying this to AI stocks going forward…

The key point is that we don’t actually need to know in advance which companies will ultimately win or lose.

Think back to the examples we just walked through. Adobe looked like a dominant software franchise for years. Kratos was a relatively obscure defense contractor that most investors barely discussed. Yet price ultimately revealed their respective truths long before the broader narrative caught up.

And that’s the beauty of this framework.

You don’t have to correctly predict the future of AI.

You don’t have to perfectly forecast which business models will be disrupted and which will thrive.

The market will begin revealing those answers through price long before they appear in headlines or earnings reports.

If you’re anchored to your own predictions and biases, you’ll likely miss those shifts. But if you’re anchored to price, you simply adapt.

Bottom line: With this market approach, price becomes your compass, and stage analysis becomes your map. Together, they allow you to stay nimble as this AI revolution sorts out its winners and losers.

How to apply it today

At a very basic level, the process is simple.

First, look for stocks that have spent weeks or months moving sideways in a tight range. That’s often the hallmark of a Stage-1 consolidation.

Second, watch for a decisive breakout above that range on strong volume – roughly two to three times normal trading volume. When institutions begin accumulating shares, those breakouts can launch the kind of sustained Stage-2 advances that drive the biggest gains.

Also, be aware of a stock’s inherent volatility so that you aren’t shaken out of a trade prematurely. You don’t want to mistake normal volatility for a breakdown.

That’s the basic blueprint. And you can begin using it today.

However, the challenge is scale.

There are thousands of publicly traded stocks. At any given moment, only a small fraction are transitioning from consolidation into breakout mode. And spotting them early requires scanning hundreds – sometimes thousands – of charts.

That’s why Luke built a systematic breakout screener with his team.

Instead of manually combing through the market, the tool scans more than 3,000 stocks and assigns each one a breakout score from 1 to 5 based on momentum strength and stage positioning.

The highest-scoring stocks are the ones most likely to be on the verge of entering a powerful Stage-2 move.

Here’s the example we provided in yesterday’s Digest from augmented reality smart glasses company Vuzix (VUZI). It gets a “5” today, meaning it is highly primed for a breakout.

For a deeper dive into this trading framework, Luke just released a free presentation where he walks through how it works, what Stage 2 looks like on a chart, and which stocks are scoring highest right now.

And if you join him, you’ll get unlimited access to this new breakout stock screener. You can use it to find your own Stage 2 stocks.

Circling back to the prospective winners and losers from AI

The market is already beginning to separate AI’s winners from its casualties.

As we look at both groups, let’s begin with the stocks Luke just flagged as casualties caught up in the carnage of the rotation out of “digital” AI.

From Luke:

Atlassian (TEAM), Flutter (FLUT), HubSpot (HUBS), Intuit (INTU), Workday (WDAY), Reddit (RDDT), Zillow (Z), DraftKings (DKNG), Robinhood (HOOD), TheTradeDesk (TTD), ZScaler (ZS), Pinterest (PINS), ServiceNow (NOW), Figma (FIG), Expedia (EXPE), Salesforce (CRM), SoFi (SOFI), Adobe (ADBE).

Every single one of these stocks is down more than 30% in 2026. We’re barely into March.

That’s not a correction. That’s a repricing.

On the other hand, here are a handful of the recent winners of this rotation that Luke flags:

• SanDisk (SNDK)
• BloomEnergy (BE)
• Moderna (MRNA)
• Generac (GNRC)
• Modine (MOD)
• WesternDigital (WDC)
• Entegris (ENTG)
• MKS (MKSI)
• ComfortSystems (FIX)

But these are stocks that have already made big moves. We want to focus on what happens going forward.

Back to Luke for a few more ideas:

Look at:

• Taiwan Semiconductor (TSM), whose fabrication plants represent decades of accumulated manufacturing knowledge that no competitor can replicate in under a decade.
• Constellation Energy (CEG), whose fleet of nuclear reactors is now signing 20-year power purchase agreements directly with Microsoft (MSFT) and Meta (META) because hyperscalers need 24/7 carbon-free baseload power and there are simply not enough nuclear plants on the planet.
• Eaton (ETN), GE Vernova (GEV), Arista Networks (ANET), Micron (MU), Cameco (CCJ): These companies don’t just have physical moats – they have direct revenue tailwinds from AI spending.

To be clear, the goal isn’t to blindly buy any stock on Luke’s list

Instead, think of these names as a watchlist – companies sitting directly in the path of AI spending.

From there, stage analysis can help determine when heavy buying pressure is moving them.

If one of these stocks breaks out of a consolidation with strong volume, that could signal the start of a Stage-2 advance. If it breaks down, price will tell you that story just as clearly.

That’s why combining Luke’s research with a stage-analysis framework can be so powerful…

The right stocks…at the right time.

Bottom line: AI’s pathway of destruction – and opportunity – rolls on. Make sure you’re prepared.

Have a good evening,

Jeff Remsburg

(Disclaimer: I own MSFT.)

The post The Stocks Poised for a Breakout appeared first on InvestorPlace.

Better chips. More data centers. AI-powered robots.

They’d all be wrong.

Because none of those things work without electricity.

Before any of that happens, we need power.

A lot more power.

That’s why this week, President Trump brought several of the most powerful technology leaders in the world back to the White House.

What makes that remarkable is that many of these same executives were among his fiercest critics just a few years ago.

But artificial intelligence is changing the equation.

AI is advancing so quickly that electricity is becoming the limiting factor.

And if the United States wants to maintain leadership in AI, we will need vastly more power to run the data centers that make it possible.

In today’s ÃÛÌÒ´«Ã½ 360, I’ll explain why electricity is emerging as the most important constraint in the AI Revolution, what Big Tech and the White House plan to do about it – and why the companies positioned at this bottleneck may hold enormous strategic leverage as the next phase of AI unfolds.

AI’s Infrastructure Arms Race

This meeting raises an important question: Why has energy become central to the AI conversation?

The answer is simple. The AI boom is no longer just a software story; it is an infrastructure arms race.

Technology giants are competing to build larger models, deploy them faster and scale them globally. Each new generation of AI systems requires dramatically more computing power than the last. What began as a software breakthrough is now a race to build the physical backbone that enables advanced AI.

But there is a constraint that few investors are focusing on.

Training advanced models consumes vast power. Deploying them at scale consumes even more.

And that reality is becoming impossible to ignore.

According to Axios, nearly 3,000 data centers are currently under construction or planned across the United States – on top of roughly 4,000 already in operation. Power consumption in the U.S. is projected to hit record highs in 2026, with some forecasts suggesting we will need the equivalent of 15 to 20 new power plants just to keep up with AI’s appetite.

In many regions, utilities cannot expand capacity fast enough to meet rising demand. Transmission upgrades take years. Interconnection queues are backed up. And in some areas, the grid is already operating near capacity.

This is the backdrop behind this week’s meeting at the White House.

Artificial intelligence is increasingly viewed as a strategic industry. But leadership in AI requires scale, and scale requires electricity.

That creates pressure.

Pressure on the grid. Pressure on utilities. Pressure on prices.

And both policymakers and technology leaders understand that this constraint cannot be ignored.

That’s why, this week at the White House, the companies agreed to what the administration called a “ratepayer protection pledge.”

The idea behind the agreement is simple.

Rather than relying entirely on local utilities – and potentially driving up household electricity costs – the companies pledged to build, buy or finance the power needed to run their AI data centers themselves.

In other words, they will increasingly supply their own electricity.

The goal is to ensure that the rapid expansion of AI infrastructure does not push up energy costs for consumers – an issue that has begun to draw scrutiny from regulators and local communities.

In announcing the agreement, President Trump said the pledge would allow the United States to maintain “the most advanced A.I. infrastructure on the planet without American families being forced to pick up the tab.”

The Solution AI Builders Are Turning To

So how exactly are these companies going to deliver on the promise they just made?

The answer is relatively simple: They are generating their own power.

They can’t afford to wait years for new transmission lines or utility approvals. What’s more, even brief disruptions can ripple through enterprise systems, customer platforms and mission-critical applications.

Reliability is non-negotiable.

That’s why many companies are now turning to distributed, on-site generation systems that can be deployed directly at data centers, independent of broader grid constraints.

This offers several strategic advantages:

• Speed. On-site systems can often be deployed far faster than new transmission projects or centralized power expansions.
• Resilience. Generating electricity at the point of use reduces exposure to grid congestion and regional instability.
• Scalability. As AI workloads expand, capacity can be added incrementally, allowing infrastructure to grow alongside demand.

This helps explain why the companies enabling this shift are quietly moving into a position of enormous strategic leverage.

Because when the world’s largest technology firms suddenly need vast amounts of reliable energy, the businesses that can supply it become incredibly valuable.

In fact, one of the companies positioned at this critical junction is a stock I already follow closely. I recently wrote a special report explaining why companies like this could become major beneficiaries of the AI power boom.

That’s especially true when you consider what’s on the horizon…

Project Apex: The Next Stage of AI

See, the demand for power is about to accelerate even further.

Because soon, a project I’ve been calling the “ChatGPT Killer” is about to take the world by storm.

I recently tested this new AI breakthrough to see what it was all about.

And what I saw left me stunned.

Not only does it represent a major upgrade in AI. But as soon as the rest of the industry learns about it, they’re going to scramble to catch up.   

In my latest special briefing, I explain the importance of this new breakthrough, why this phase of AI may be the most critical yet – and how investors can position themselves to profit from the companies at the center of it.

Go here to watch it now.

Sincerely,

Louis Navellier

Editor, ÃÛÌÒ´«Ã½ 360

The post What Big Tech’s White House Meeting Means for the Next Stage of the AI Boom appeared first on InvestorPlace.

As the U.S.-Iran conflict continues to escalate, the investment world has become hyper-focused on how high oil prices can go.

Some analysts even predict that oil could rise to $100 or beyond if the conflict lasts longer than three weeks.

Now, we don’t know what will happen in energy markets past that horizon – in fact, no one does. All we can say is that there’s a long history of people wrongly estimating how conflicts in the Middle East will turn out.

In the meantime, we feel our time is better spent on analyzing things we can predict… like the world-changing transformations happening thanks to AI.

For the last few years, Eric has been monitoring AI’s growth toward artificial general intelligence (AGI) – the moment when artificial intelligence develops superhuman intelligence.

Superintelligent AI is already creeping into our lives, though it’s not been a single “aha” moment. Instead, AGI is like how OthersideAI CEO Matt Schumer described it in a now-viral blog post:

It’s like the moment you realize the water has been rising around you and is now at your chest.

For me, that moment began in 2025 when AI firms started using artificial intelligence to recursively improve themselves.

But everything began to fall into place only in the past several months.

With enough handholding, frontier models were becoming good enough to re-create the quantitative financial models I had developed several years ago.

Now, I can simply give Claude Code enough financial data, ask it to build something, and sit back as it runs off by itself to write thousands of lines of code.

So today, I’d like to discuss these important AI advancements and how they’re giving us a taste of what’s to come.

But more specifically, I want to bring to your attention a streaming giant that accounted for over 95 billion hours of viewing time in the first half of 2025. Alarmingly, even this household name is vulnerable to AI’s disruption.

Then, I’ll show you how to find the companies that can withstand the future of AI…

AI’s Growing Takeover

AI is becoming less like a robotic mecha-suit that needs a human pilot and more like a fully autonomous machine that can replace entire teams of analysts and coders.

The same is proving true for virtually every knowledge-based industry…

• Law. Last month, veteran lawyer and former litigator Chad Atlas described how it’s now possible to upload entire contracts into Claude Cowork for review.
• Healthcare. Cancer-detecting AI is becoming as good or even better than human doctors, according to numerous studies.Some experts like physician-scientist Eric Topol are now essentially calling for mandatory AI incorporation in mammogram screenings.
• Accounting. AI tools are replacing entry-level audit roles, according to Carl Mayes, vice president at the American Institute of Certified Public Accountants (AICPA), the professional organization overseeing public accountants.

This is why we’ve seen so many software-as-a-service (SaaS) companies get pummeled in the past several weeks. Investors are suddenly faced with the real-life version of what futurists have warned about for years.

And one popular streaming service giant is particularly susceptible to AI competition. Many analysts rate this stock a “Buy,” so we want to warn you about this household name ahead of time…

This “Buy”-Rated Stock Is a “Sell” in Disguise

I’m talking about Netflix Inc. (NFLX).

Shares of the online streaming firm shot up almost 30% last week after dropping its bid to buy Warner Bros Discovery Inc. (WBD). Netflix’s stock price is now back to where it was in early 2025, valuing the streaming firm at 38X earnings – twice as high as the figure achieved by Walt Disney Co. (DIS) and right at its four-year average.

Investors clearly aren’t worried about the streaming company’s long-term ability to generate more profits. Neither are Wall Street analysts, which have 37 “Buy” ratings on the stock (compared to 13 “Holds”).

However, Netflix operates a very similar model virtually every other consumer-focused SaaS company. The firm creates digital products (in this case, movies and shows) and delivers them to users on a subscription basis. These monthly charges are cancelable at any point.

That makes Netflix extremely sensitive to AI competition.

Think about it. Their moat comes from making engaging, high-quality video content that users happily pay $17.99 a month to access.

What happens when people on their laptops can create feature-length films using AI? At that point, it’s hard to imagine Netflix charging much of a premium for its human-acted content.

“But AI video is slop,” some might counter. “And what about scriptwriting, acting, and consistency?”

Here’s where some imagination is needed.

Video AI models today consistently make errors and are limited in length. But that’s also what many said about early language and image models. And look where those models are today.

Seedance 2.0, the Chinese-owned AI video generator that created a viral, buggy clip of Jackie Chan fighting Jet Li, will be replaced in short order by an even better model.

An AI scene by Seedance 2.0

Besides, these AI firms have access to virtually every movie and TV show ever made… not to mention all the millions of professional reviews and billions of online comments people make about the quality of these shows.

Once enough computing power is installed, there’s nothing stopping an AI from generating a near-infinite number of TV show scripts, turning the top few into test screenplays, acting the whole film with deep-faked actors (or its own character creations), and then iterating on the top versions until it creates a feature-length film that its own AI review process rates as nearly perfect.

That’s the future Netflix faces.

So, instead of potentially getting burned by an investment that could follow the same volatile path as SaaS companies, I urge investors to begin looking elsewhere.

How to Build a Portfolio AI Can’t Disrupt

Hundreds of other firms like Netflix could face the same future, not to mention the millions of employees of these companies who may soon find themselves redundant.

Could AI eventually build entire e-commerce businesses from scratch?

Run a full-scale telehealth business?

Create live TV news?

I believe the answer is “yes” to all the above… and more. That’s because AI models can already do most of the work.

Furthermore, I see only three key factors missing from turning current-generation AI into full-fledged companies…

That’s why Eric and I have been talking so incessantly about the strong companies that can withstand significant disruptions of artificial intelligence… and eventually AGI.

These firms are not always popular, nor are they always in fast-growing industries.

Nevertheless, we believe the underappreciated firms in the Fry’s Investment Report portfolio are immune to any near-term effects from AI.

No matter how “boring” Eric’s energy, basic materials, and even consumer sector holdings may seem… they’re not going to be replaced anytime soon by AI.

And that’s the whole point.

Click here for more information on how to bulk up your portfolio and survive the AI Revolution.

Until next time,

Thomas Yeung

ÃÛÌÒ´«Ã½ Analyst, InvestorPlace

The post The Stock Everyone’s Buying That AI Will Destroy appeared first on InvestorPlace.

When Block (XYZ) announced it would eliminate 4,000 employees – roughly 40% of its workforce – the stock surged 24% after hours and added billions of dollars in market value.

In almost any other era, that reaction would have seemed grotesque. Today, it looks like a preview of the AI economy.

This shockwave didn’t come because the business was struggling but because, in Dorsey’s own words, “intelligence tools have changed what it means to build and run a company.” 

And it tells us almost everything we need to know about what is coming…

Because this wasn’t just a layoff announcement.

This was a signal.

While companies cut staff all the time – restructurings, downturns, pivots, the occasional spectacular implosion – this was different in kind. Dorsey didn’t apologize his way through a financial crisis. He didn’t blame macroeconomic headwinds or “right-sizing” for a post-pandemic reality. He said, plainly and with apparent genuine conviction, that AI had made thousands of his employees unnecessary – and that within a year, most CEOs would arrive at the same conclusion.

“I’d rather get there honestly and on our own terms,” he wrote, “than be forced into it reactively.”

He’s probably right. And that is exactly the problem.

The Competitive Domino Effect Now Facing Fintech

Let’s be clear about what likely happens next.

Block’s direct competitors – PayPal (PYPL), Shopify (SHOP), Stripe, Adyen (ADYEY), Clover, Toast (TOST) – are watching this announcement very carefully. Dorsey just gave them cover. 

The moment one major player in a competitive market achieves structurally lower operating costs through AI-driven headcount reduction, the others face a binary choice: match the efficiency or compete at a permanent cost disadvantage. In a low-margin, high-volume industry like payments, that’s not really a choice at all.

So, fintech will cut. Then the competitive pressure radiates outward to the broader financial services sector – to the payment processors, banks, insurance companies, and asset managers who have been nervously watching AI productivity metrics for two years and quietly hoping someone else would go first. 

Block just went first. Others will follow.

The logic that applies to fintech also applies to software, consulting, media, law, accounting… any industry where people are paid to think. 

That is the knowledge economy. It employs tens of millions of Americans across finance, technology, consulting, media, and professional services.

And it is now facing an existential crisis from AI. 

You see – Dorsey didn’t just fire 4,000 people. He fired the starting gun.

To understand how large that shift could become, we ran the numbers.

Modeling the AI Layoff Scenarios

Using Block as an anchor, we modeled the employment implications across three frameworks. The results are not encouraging.

Framework 1: Pre-COVID Headcount Reversion

At the end of 2019, Block employed 3,835 people. It grew to over 10,000 by 2025 – a 174% increase – before cutting back to 6,000. If AI allows companies across the knowledge economy to revert to their pre-pandemic headcounts, the math implies a moderate but significant employment shock. 

Depending on how aggressively you model the overhiring and how many displaced workers find new roles, total U.S. unemployment could plausibly land somewhere between roughly 5% and 8% – a mild-to-severe recession range. 

This is the most conservative framework, because most knowledge economy companies didn’t grow as aggressively as Block during COVID.

Framework 2: Revenue-Per-Employee Shock

Block’s post-cut revenue per employee improves by roughly 75% relative to its pre-cut level. Apply that productivity gain – scaled to realistic adoption rates across the broader knowledge economy – and you get potential unemployment outcomes between 8% and 16%, with the middle scenario of 50% productivity gains producing roughly 12% total unemployment. 

That exceeds the peak of the 2008 financial crisis.

Framework 3: The 40% Headcount Reduction Scenario

If we assume fintech follows Block, cutting 40% of headcount, and the broader knowledge economy achieves a 30- to 40% reduction, total unemployment could run 9% to 13%, with the moderate-to-aggressive scenarios consistently pushing above 10%.

Across all three frameworks, the most likely range is 8% to 13% total U.S. unemployment – with the most defensible central case somewhere around 10- to 11%. 

To be precise: these are total unemployment rates, including today’s baseline of 4.2%. The AI-attributable increment is roughly six to nine percentage points above the current level.

In these scenarios, the unemployment rate for the knowledge economy in particular runs between 15- and 23%. Think about that. College-educated, white-collar professionals – the people who were told that education was the hedge against technological displacement – experiencing Great Depression-era joblessness in their specific labor market.

These are the hard numbers we could soon be facing if Block just created the new labor framework for the Age of AI. 

Why AI Job Losses Could Be Structural – Not Cyclical

In every recession throughout American history, the implicit promise has been that the jobs come back. 

Cyclical unemployment is painful but temporary. The economy contracts, the Fed cuts rates, demand recovers, hiring resumes. In most downturns, displaced workers eventually find their way back into the labor market. After the COVID shock of 2020, for example, restaurant employment rebounded quickly once demand returned. Even after deeper recessions, new jobs eventually emerge to absorb displaced workers.

But what Block has announced is not cyclical. It is structural. The jobs are not coming back because the need for those jobs no longer exists. A 50-person team doesn’t need to regrow from 30 when the economy recovers – it can stay lower because AI handles what the other folks used to do. The productivity gain – and the displacement – is permanent.

This means the traditional escape valves don’t work. 

Retraining into the skilled trades is often floated as the obvious solution. And for some displaced workers, it will be. But large-scale labor transitions rarely happen as smoothly as policy discussions suggest. Skilled trades require years of apprenticeship, physical conditioning, and geographic flexibility – not something millions of mid-career professionals can pivot into overnight. And even that path may not be immune for long. 

The next wave of AI isn’t just software; it’s robotics. Companies from Tesla (TSLA) to Figure AI are racing to scale humanoid robots designed specifically for physical work. If those systems mature over the next decade, the same forces disrupting white-collar jobs today could eventually start reshaping parts of the trades as well.

And the “AI creates new jobs” argument, while historically valid in other technological revolutions, faces a structural challenge it has never faced before. Every previous automation wave left humans with a comparative advantage in creativity, judgment, and complex reasoning. AI is attacking precisely those capabilities. The historical analogy may simply not hold.

What we would get instead is bifurcation. A small cohort – perhaps 10- to 15% of displaced workers – successfully pivots to AI-adjacent roles: prompt engineering, AI training, model evaluation, the genuinely irreplaceable functions of high-trust human relationship management. 

The rest face a very different reality – one the American social contract has little institutional language for.

What a 10% AI-Driven Unemployment Economy Might Look Like

Believe it or not, in this scenario of ~10% structural unemployment, GDP probably looks fine. Maybe even good. 

Productivity gains flow into corporate output, margins expand, earnings grow, and GDP – which measures production, not welfare – ticks upward at 2- to 2.5% annually. The headline number will be used, relentlessly, to argue that everything is working. It is not a lie. It is something worse than a lie: a true statement that obscures a catastrophe.

The stock market, in the near to medium term, goes up. Every Block-style announcement is a double-digit after-hours pop. Every CEO who announces AI-driven headcount reductions is rewarded by shareholders. The S&P 500 could be at 7,000… 8,000… even 9,000… while 12% of the country is structurally unemployed. 

Both things will be true simultaneously. The cognitive dissonance will be extraordinary.

Wealth inequality moves from “already alarming” to “historically unprecedented.” The labor share of GDP – currently around 60% – compresses toward 45- to 50% as productivity gains accrue to capital rather than workers. Stock ownership, concentrated overwhelmingly in the top 10% of the wealth distribution, means that rising markets directly transfer wealth upward. 

The U.S.’ Gini coefficient – a measure of income inequality where 0 represents perfect equality and 1 represents maximum inequality – is already among the highest in the developed world at 0.49. Wealth inequality is even more pronounced, with a Gini coefficient of roughly 0.83. Both could continue rising toward levels historically associated with periods of significant social and political instability.

That is the future. And it seems imminent. 

The Petro-State Parallel: When Capital Replaces Labor

Step back from the modeling for a moment, and the bigger structural shift comes into focus.

There is a historical analogy for an economy that generates enormous wealth from a highly productive, capital-intensive sector that employs relatively few people: the petro-state.

Saudi Arabia. Kuwait. Venezuela before its collapse. In these economies, oil – not labor – created most of the national wealth. 

The oil sector itself employed surprisingly few people compared to the wealth it generated. Governments often redistributed that wealth through public-sector jobs, subsidies, and social programs.

The emerging AI economy could start to resemble parts of that structure. 

A small number of companies – the hyperscalers, the foundational model providers, the AI-native platformers – generate extraordinary output with minimal labor. The core infrastructure layer of the AI economy simply may not require millions of workers.

That raises a question resource economies have faced for decades: if a narrow slice of the economy generates most of the wealth, what role does everyone else play in the system?

Many petro-states addressed that imbalance through redistribution funded by resource revenues, often alongside highly centralized – sometimes authoritarian – political systems. In many Gulf states, resource wealth effectively purchased social stability. Citizens received economic benefits funded by oil revenues while political participation remained relatively limited.

The United States could face a version of this tension from a very different starting point.

The workers most exposed to AI disruption are not populations that historically expected redistribution. They are knowledge workers who were told – repeatedly – that education was the path to economic security. Many accumulated significant student debt on that premise. They built professional identities, social status, and financial lives around the assumption that the knowledge economy would continue to need them.

If that assumption changes quickly, the adjustment could be complicated. 

Modern advanced economies have very little precedent for navigating this kind of transition. And policymakers are only beginning to grapple with what it might mean.

Who Wins In the AI Economy

Feb. 26, 2026 may eventually be remembered as an early signal that the structure of human labor was beginning to change, and Block’s Dorsey was simply the first to act on it honestly.

The restructuring of the U.S. labor market that follows will produce an equally fundamental restructuring of the U.S. economy. The specific contours remain genuinely uncertain. The political response – ranging from aggressive redistribution to authoritarian reaction to some combination of both – will shape the outcome as much as the technology itself. 

The timeline, magnitude, and societal repercussions remain unclear.

What is decisively not unclear is who benefits from the transition itself, regardless of how it resolves. 

The companies that build the infrastructure of the AI economy – the foundational model makers, the hyperscalers who provide the compute, the semiconductor manufacturers whose chips are essential to this new economy, the energy companies and data center builders who power the whole apparatus – are the functional equivalents of whoever held the mineral rights when oil was discovered.

In a world where intelligence becomes a commodity produced by machines, the machines – and the companies that own them – win.

The question of what happens to everyone else is the most important political and social question of our lifetimes. 

It doesn’t have an answer yet. But Jack Dorsey just forced it into the open.

And while policymakers argue about the consequences, the investment implications are already becoming clear.

The companies building the infrastructure of artificial intelligence – the models, the chips, the data centers – are becoming the economic backbone of the next era.

And the company most closely associated with that transformation may soon give investors their first real chance to buy in.

OpenAI is widely expected to enter public markets this year. When it does, it could become the first true “AI platform” stock – the equivalent of owning the operating system of the intelligence economy.

I’ve identified a way investors may be able to position themselves before that moment arrives – before the IPO headlines, before the Wall Street frenzy, and before passive funds rush in.

You can learn how it works right here.

The post Block’s Layoffs Reveal the Dark Side of the AI Economy appeared first on InvestorPlace.

Most investors didn’t see it.

And even if they noticed, the story quickly disappeared from the headlines as the conflict with Iran took over the news cycle last weekend.

But last Thursday, Block (XYZ) did something unprecedented – it announced the largest corporate layoff (by percentage) in the recorded history of the S&P 500.

40% of workers eliminated.

Why?

Block CEO Jack Dorsey was clear:

Today we’re making one of the hardest decisions in the history of our company: we’re reducing our organization by nearly half…

We’re not making this decision because we’re in trouble. Our business is strong…

Something has changed…

That “something” is AI.

Dorsey explained that the intelligence tools they’re building – combined with smaller, flatter teams – fundamentally change what it means to run a company.

Luke Lango, our technology expert and editor of Innovation Investor, put it bluntly:

This is the first domino. Because Dorsey is right.

AI has changed the rules of running a business. You just don’t need as many people anymore…

Dorsey just broke the dam.

For more than a year in the Digest, we’ve urged readers to recognize the profound shift in the corporate landscape that’s heading toward us.

While many analysts argue that AI will follow the pattern of past technological revolutions – where the jobs displaced were ultimately replaced by new roles the innovation created – we’ve disagreed.

That’s because we’ve never faced a technology capable of performing nearly every human task better, faster, and at a lower cost. And that means substantial labor market disruption is on the way.

Here’s Luke with the potential scope:

Our modeling suggests we will be looking at 8%-13% structural unemployment.

This, of course, has massive economic, societal, and market implications. 

But the “north star” idea here is that the labor class will increasingly lose wealth while the capital class will increasingly gain wealth (so be in the capital class – own stocks). 

I’ll be doing all I can to share our analysts’ ideas on the best stocks to own as AI radically reshapes our world. But let’s look a bit further out on the horizon to a looming risk – even if you own AI stocks.

The coming “gray” swan

You’ve heard of a black swan – a rare, unpredictable event.

What’s ahead in AI isn’t quite that. It’s more of a “gray swan” – an event that’s highly probable, though the exact details of how we get there, and when, are unclear.

In this case, the event is legislation that slams the brakes on AI’s buildout, leading to a massive market shakeout. What’s unclear is what will precipitate it.

I see two highly likely potential paths:

1. Political Backlash from Job Losses

If layoffs accelerate as Luke predicts, public pressure will mount on politicians to step in to do something to protect jobs. Wanting to keep their own jobs, elected officials – even those who support AI – will be forced to swing into action.

The core issue here is public sentiment. So, where are we on that today?

Let’s go to The Wall Street Journal from Saturday:

Backlash to AI has been simmering for months.

In a YouGov survey released in December, 77% of respondents said they worried AI could pose a threat to humanity.

A separate survey from the Pew Research Center showed many people were more concerned than excited about AI.

Fearing higher utility costs or job losses, communities around the country have sought to block or delay new data-center projects, part of growing resistance to such projects.

Unchecked, this public outcry will only increase.

This issue is already on the radar for some politicians. Last November, Senators Josh Hawley, R-Mo., and Mark Warner, D-Va., introduced the AI-Related Job Impacts Clarity Act. It would force companies to report AI-related job cuts to the U.S. Department of Labor (DOL).

Here’s Hawley:

Artificial intelligence is already replacing American workers, and experts project AI could drive unemployment up to 10% to 20% in the next five years.

The American people need to have an accurate understanding of how AI is affecting our workforce, so we can ensure that AI works for the people, not the other way around.

But spiking joblessness is just one concern that could spur new legislation. As disruptive as 20% unemployment would be, the second path could even more chaotic…

2. A Crisis Event

The second path involves a true shock – a visible failure or misuse that makes AI risks undeniable overnight. Think a “Three Mile Island” meltdown scenario for AI.

Last December, President Trump issued an Executive Order emphasizing minimal barriers to U.S. AI leadership:

United States AI companies must be free to innovate without cumbersome regulation…

It is the policy of the United States to sustain and enhance global AI dominance through a minimally burdensome national policy framework.”

This “all gas, no brakes” posture accelerates innovation, but it also increases risk.

Technology ethicist Tristan Harris, the central figure of the 2020 Emmy-winning Netflix documentary The Social Dilemma, described the dynamic in stark terms:

“Let It Rip” means to open-source, deregulate, and accelerate AI’s benefits into every corner of society.

But it also unleashes chaos.

Floods of deepfakes and AI-generated content overwhelm our information environment. Frauds and scams skyrocket.

AI increases hacking capabilities that makes critical infrastructure more vulnerable. AI enables bad actors to do dangerous new things with biology. 

Meanwhile, former-Googler Geoffrey Hinton, often cited as the “Godfather of AI,” put it far more directly:

Politicians don’t preemptively regulate.

So, actually, it might be quite good if we had a big A.I. disaster that didn’t quite wipe us out – then, they would regulate things.

Bottom line: Whether our gray swan is economic pain or a singular crisis moment, the outcome would likely be the same…

Sudden, sweeping governmental regulation.

So, what happens to your AI stocks?

Well, AI won’t stop – it will simply become concentrated after a painful shakeout.

Yes, Wall Street will sell first and ask questions later. So, nearly every AI-tied stock would likely get hit in the initial drawdown. It will be hard to protect against this entirely.

The biggest losses will go to software platforms, high-multiple application plays, and “AI-adjacent” consumer names. Those are especially vulnerable as investors reassess growth assumptions overnight.

But here’s the part of the AI trade that won’t disappear:

• Data centers
• Advanced semiconductors
• Power generation
• Critical minerals and rare earths

This “physical backbone” of AI will remain mission critical.

In fact, if regulation tightens, AI development would likely become more centralized, shifting toward government oversight and strategic partners.

Luke reminds readers that we’ve already seen Washington take equity stakes in key companies tied to AI and national security, and the market reaction has been explosive:

• MP Materials soared 50% in a single day after the Pentagon bought a stake.
• Lithium Americas doubled overnight, jumping 100% when the Department of Energy bought in.
• Trilogy Metals didn’t just double; it tripled overnight after the government wrote the check.

So, this is where Luke is urging investors to focus their AI investment dollars today. After all, though legislation would slam the brakes on much private-sector AI spending, it won’t stop the White House.

For Luke’s specific portfolio action steps, he just released a video briefing that compiles all his research on 119 companies – including their names, ticker symbols, buy-up-to prices, and the top 5 to buy right now. It’s in his report, The President’s ÃÛÌÒ´«Ã½.

As he puts it:

If you’re not watching what Washington is buying, you’re already behind.

But there’s another reality to this potential for legislative disruption

When this gray swan hits, we won’t see an orderly transition in the markets. We’ll see a convulsion.

Leadership will flip. Momentum will surge and fade as the market adjusts. And former Wall Street darlings could break down fast while entirely new names enter powerful breakout phases.

That kind of environment doesn’t reward complacent buy-and-hold investing. It requires agility.

That’s why Luke just launched something in addition to his physical layer/government AI research – it’s a breakout-focused trading framework built specifically for today’s structurally volatile market.

Basically, instead of trying to forecast winners many quarters away, this strategy is all about now.

It targets stocks entering what technical traders call “Stage 2” – the phase where major price runs historically begin.

You see, at any given point in time, a stock is in one of four unique stages: 1) going sideways at a bottom, 2) going up, 3) going sideways at a top, or 4) going down.

The key to scoring consistently big returns in the market – and navigating leadership shifts in the market – is to find stocks already in, or are on the cusp of entering, Stage 2…and then getting out with your profits before Stage 4.

To help investors and traders with this, Luke and his team just opened access to:

• A brand-new breakout stock screener scoring 3,000+ stocks on a 1-5 scale
• A weekly breakout watchlist highlighting top momentum candidates (the top 10 scoring stocks on the screener)

Here’s an example, using augmented reality smart glasses company Vuzix (VUZI). It gets a “5” today, meaning it is highly primed for a breakout.

I’ll bring you additional details in tomorrow’s Digest, but if you’d like to dig deeper right now, Luke just released a new video that lays out why volatility won’t be going away anytime soon – and how a Stage-2 framework can turn that volatility into a tailwind.

Wrapping up

AI’s advance isn’t in question. What’s uncertain is the path it takes – and how quickly a gray swan event may force that path to change.

If the AI transformation unfolds gradually, capital will continue flowing steadily into the infrastructure that powers it – chips, data centers, energy, and critical materials.

If it deviates from that path suddenly – through surging unemployment or a crisis event – markets will lurch, leadership will rotate, and volatility will spike before a new equilibrium forms after legislation.

Either way, our safest takeaway remains the same…

Own/trade what’s essential… stay alert to shifts in momentum… and be prepared to adapt as conditions change.

The investors who combine longer-term structural positioning with shorter-term tactical flexibility will be the ones who navigate this transition best.

Have a good evening,

Jeff Remsburg

The post AI’s “Gray Swan” Risk appeared first on InvestorPlace.

According to Luke Lango, we’ve entered a new market regime – one dominated by algorithms, high-frequency trading, retail flows, and rapid narrative shifts driven by technology.

Volatility isn’t just a temporary phase. Now, it’s the default setting.

For decades, investors were told to focus on fundamentals, buy great companies, and hold on for the long haul. That approach still has its place, but it can come with gut-wrenching drawdowns and years-long recovery periods in today’s environment.

Meanwhile, some of the market’s biggest gains now tend to occur in concentrated bursts… when a stock shifts from consolidation into what market technicians call “Stage 2,” the advancing phase of a breakout.

That’s why I invited Luke to explain this investment method in today’s guest essay…

In it, Luke discusses why he believes the volatility isn’t temporary, but structural… why leadership rotates faster than ever… and why identifying stocks as they enter Stage-2 momentum could dramatically improve returns.

You don’t have to abandon long-term investing to consider a tactical overlay. But if you’ve felt the market’s whiplash (and wondered whether the old playbook is enough), this perspective is worth your time.

Take it away, Luke…

There’s a quiet panic spreading through the investing world.

It doesn’t show up in headlines. But you hear it in planning offices and investor forums:

“Why doesn’t this make sense anymore?”

It’s that moment when your watchlist is green at 10:30… red by lunch… and back to flat by the close — and you can’t even point to a single piece of news that explains the entire round trip.

Or when a stock reports “good” earnings, sells off anyway, then rips higher two days later — not because anything changed in the business, but because money moved.

That disconnect is what’s unnerving people. Not volatility by itself… but volatility that feels unmoored, like the market is reacting to forces most investors can’t see.

The media focuses on AI companies and job disruption. But the deeper shift is happening inside the market itself.

Stocks move faster. They reverse harder. And they disconnect from fundamentals more violently than at any point in modern history. The strategies that built wealth for decades can still work — but they no longer work the way investors remember.

ÃÛÌÒ´«Ã½s that once moved in days now move in minutes. Sometimes seconds.

“Buy great businesses and wait” still works over long stretches. But it now requires enduring drawdowns many investors simply can’t stomach.

Algorithms are now the market.

They account for roughly 70% to 90% of daily U.S. equity volume. Add a surge in retail participation — with stock cash flows running more than 50% higher last year — and you get a system wired for speed and sharp swings.

The human beings you picture on a trading floor — reading tape, making calls, “deciding” what happens next — are mostly the last visible layer of the system.

The real decision-making is increasingly automated, happening in data centers where machines react to headlines, prices, and order flow faster than any person can process.

That doesn’t mean “humans don’t matter.” It means the first move often happens before humans even agree on what the story is.

The average holding period has collapsed from roughly eight years in the 1950s to about five months today.

Since COVID, we’ve experienced three bear markets — roughly one every two years.

That’s not a temporary phase. It’s structural.

And it may intensify. ÃÛÌÒ´«Ã½s are evolving beyond rule-based algorithms toward agentic AI systems that react to data — and to one another — in real time.

So what happens when price and fundamentals drift apart?

Blue-chip stocks like Netflix Inc. (NFLX) and Nvidia Corp. (NVDA) have lost 35%, 50%, even 60%+ before recovering.

Nvidia alone has endured four major crashes in eight years. The stock ultimately advanced — but holding through those drops required unusual discipline.

Most investors don’t “just hold.” They sell low and buy back higher. Loss aversion is powerful — and expensive.

Meanwhile, price behavior has grown increasingly detached from business performance. Opendoor Technologies Inc. (OPEN) rallied nearly 1,900% in two months despite deteriorating fundamentals.

Zillow Group Inc. (Z), another real estate tech firm with stronger revenue and market position, barely moved.

When price decouples from fundamentals, traditional analysis becomes unreliable.

Here’s how you operate in a market like this…

Stage Analysis: Built for Fast ÃÛÌÒ´«Ã½s

In a high-volatility environment, valuation alone isn’t enough. What matters is where capital is flowing now.

That’s the foundation of stage analysis, popularized by Stan Weinstein.

Every stock moves through four recurring stages:

• Stage 1: Sideways consolidation
• Stage 2: Breakout and sustained advance
• Stage 3: Distribution
• Stage 4: Decline

Stage 2 is where the money is made.

Palantir Technologies Inc. (PLTR) moved from $9 to over $200 after entering Stage 2.

Carvana Co. (CVNA) surged more than 6,000% from its breakout.

Stage analysis doesn’t forecast earnings. It identifies when accumulation is already happening and momentum is building.

In a market defined by rapid rotations, recognizing a Stage 2 breakout early can mean the difference between chasing a move and positioning ahead of it.

The Real Problem: You Can’t Do This Manually

There are thousands of publicly traded stocks. At any moment, a small number are transitioning from consolidation into breakout mode.

That’s where major gains begin.

You won’t catch them by flipping through earnings reports or waiting for a TV segment. By the time they trend on social media, the move is already underway.

That’s why my team built a systematic breakout screener, which I reveal during my new free broadcast. It scans more than 3,000 stocks and assigns each a 0-to-5 breakout score based on momentum strength.

In historical testing, it flagged eight of 2025’s top-performing stocks before their major advances — including:

• Hycroft Mining Holding Corp. (HYMC) before a 1,100% run
• Terns Pharmaceuticals Inc. (TERN) before an 865% surge
• And Palantir long before it became a mainstream AI story

The objective is simple: identify stocks as institutional momentum builds — when price and volume confirm something meaningful is happening.

Volatility isn’t going away. Leadership will continue to rotate quickly.

You can try to keep up manually.

Or you can use a system designed for the market we actually have.

In my latest free presentation, I walk through how it works, what Stage 2 looks like on a chart, and which stocks are scoring highest right now. I give the name and ticker of one of those stocks away for free. Plus, folks who join me will gain unlimited access to my new breakout stock screener, which they can use to find their own Stage 2 stocks.

The market won’t slow down.

But you don’t have to fall behind.

Sincerely,

Luke Lango

Editor, Hypergrowth Investing

The post The ÃÛÌÒ´«Ã½ Moves in Four Stages — Here’s When to Move With It appeared first on InvestorPlace.

But that headline flatness is one of the most deceptive things happening in markets right now. 

Beneath that “calm” surface, a violent, relentless – and historically unusual – rotation is underway. 

On one side of the ledger: carnage. 

Atlassian (TEAM), Flutter (FLUT), HubSpot (HUBS), Intuit (INTU), AppLovin (APP), Workday (WDAY), Reddit (RDDT), Zillow (Z), DraftKings (DKNG), Robinhood (HOOD), The Trade Desk (TTD), ZScaler (ZS), Pinterest (PINS), ServiceNow (NOW), Figma (FIG), Expedia (EXPE), Salesforce (CRM), SoFi (SOFI), Adobe (ADBE). Every single one of these stocks is down more than 30% in 2026. We’re barely into March. That’s not a correction. That’s a repricing.

Meanwhile…

SanDisk (SNDK), Bloom Energy (BE), Lumentum (LITE), Moderna (MRNA), Generac (GNRC), Modine (MOD), Corning (GLW), Teradyne (TER), Western Digital (WDC), Entegris (ENTG), MKS (MKSI), Vertiv (VRT), Comfort Systems (FIX). All are up more than 50% so far this year – a parabolic move higher. 

These two groups are essentially canceling each other out. Hence: flat index. The headline number is hiding the truth in aggregation.

This isn’t a flat market – it’s an AI-driven stock rotation hiding in plain sight.

What separates the winners from the losers? Physical versus digital; atoms versus bits. The companies being demolished are pure-play digital – software, platforms, marketplaces, fintech apps. The companies soaring are manufacturers, hardware producers, and energy providers.

Wall Street has a name for this trade now. It’s called HALO: Hard Assets, Low Obsolescence.

And it’s the hottest trade on the Street in 2026. 

AI Infrastructure Stocks: The New ÃÛÌÒ´«Ã½ Leaders

Here’s where most of the conventional takes get it completely wrong.

Many are interpreting this rotation as evidence that the AI trade is dying. Tech is out, old economy is in. Growth is dead, value is back. Call your broker, and load up on coal companies. 

That story may write itself. But it’s completely wrong.

Look at the biggest winners again. SanDisk sells AI memory. Bloom Energy provides on-site backup power for AI data centers. Lumentum sells optical components for AI networking. Vertiv builds the cooling and power infrastructure that keeps GPU clusters from melting. Comfort Systems installs the HVAC systems in the data centers housing all of that hardware. 

These stocks are the physical infrastructure of AI: the wires and cooling towers and switching gear that the whole digital revolution runs on.

The AI trade isn’t dying. It’s maturing. Maturation means the market is getting far more selective about which AI stocks deserve to win.

But precision implies discrimination. And discrimination implies something far less comfortable for a lot of software businesses.

AI has become so good that it’s starting to threaten the digital economy that created it.

AI labs have recently delivered a series of leapfrog improvements – Gemini 3.0, ChatGPT 5.2, Claude Opus 4.6, Gemini 3.1 – at a pace that makes last quarter’s breakthrough feel obsolete by the next earnings call. We appear to have crossed a threshold where AI improvements are no longer incremental but compounding. And the capabilities unlocked? Truly agentic, autonomous AI; AI that doesn’t just answer questions but does things – builds software, manages workflows, writes code, runs campaigns, handles customers.

This is, plainly, an existential event for a lot of companies.

Why Software Stocks Are Getting Repriced

The tech industry spent years telling a beautiful story about AI. AI will make everything faster and smarter and better, and the companies building it will be the most profitable in history.

The market bought that enthusiastically, and a lot of software stocks went to 40x, 50x, 60x EBITDA multiples.

But there was a flip side to that pitch, which is: If AI can do everything its champions claim, it can replace everything its customers currently pay for.

That flip side has arrived. 

A company can now spin up a functional customer relationship management (CRM) system using off-the-shelf large language models in an afternoon – at the cost of a few hundred dollars a year. There’s no need to shell out $50,000/year for Salesforce. 

A startup can build a basic marketing automation stack with Claude Code in a day. So, why pay $10,000 annually for HubSpot’s marketing hub? 

A developer can generate a reasonably functional social platform with a few hours of prompting. Why rely on Reddit’s API?

These threats are real. They are accelerating, and the market is pricing them in. When investors look at a high-multiple Software-as-a-Service (SaaS) company and ask, “will this business still be here in five years?”, the honest answer is increasingly: I genuinely don’t know. And in markets, genuine uncertainty about survival tends to compress multiples aggressively. That’s why Workday and ServiceNow are down 30%-plus. It’s why Figma – a company that was valued at $20 billion 18 months ago – is now a question mark.

Atlassian, Intuit, Adobe, The Trade Desk. These are good companies facing a suddenly credible structural threat, and the market is repricing accordingly.

Why Physical Assets Are Becoming the New Moat

At the core of this rotation is a simple asymmetry: Today, AI is primarily a digital tool. It lives in software and runs on APIs. It operates in the world of information.

What it cannot do yet – and for a long time to come – is operate in the physical world at industrial scale, low cost, or with reliable execution.

ChatGPT cannot mine copper. Claude cannot build a natural gas pipeline. Gemini cannot run a nuclear reactor, pour concrete, or install cooling systems in a data center. 

This means that for the first time in about 15 years, having a physical business is a competitive advantage rather than a drag on margins. For a decade and a half, the market rewarded asset-light models – SaaS, marketplaces, platforms. Low capital requirements + high gross margins + growth = eye-watering multiples. The physical world was the slow, dumb, expensive cousin of the digital world.

Now the pendulum is swinging the other way. If your business operates in atoms – if you manufacture something, extract something, move something physical – AI is not your predator. AI is your productivity tool. It makes you more efficient, cuts your costs, helps you optimize. But it does not threaten your core reason for existing.

That’s the HALO thesis in its purest form: physical moats are the hardest moats for AI to dissolve.

HALO: Hard Assets, Low Obsolescence

Within the HALO trade, there are two distinct angles – and you want exposure to both.

HALO AI Offensive stocks are the physical picks-and-shovels of the AI buildout. These companies sell the hardware, infrastructure, and energy that AI literally cannot exist without. Think: 

• Taiwan Semiconductor (TSM), whose fabrication plants represent decades of accumulated manufacturing knowledge that no competitor can replicate in under a decade.
• Vertiv, which co-engineers the cooling systems for Nvidia‘s (NVDA) latest GPU architectures and has a $9.5 billion backlog.
• Constellation Energy (CEG), whose fleet of nuclear reactors is now signing 20-year power purchase agreements directly with Microsoft (MSFT) and Meta (META) because hyperscalers need 24/7 carbon-free baseload power and there are simply not enough nuclear plants on the planet. 
• Eaton (ETN), GE Vernova (GEV), Arista Networks (ANET), Micron (MU), Cameco (CCJ)…

These companies don’t just have physical moats – they have direct revenue tailwinds from AI spending. Every dollar Meta, Microsoft, Alphabet (GOOGL), and Amazon (AMZN) pour into data centers and AI infrastructure flows through these companies’ income statements. They get the best of both worlds: physical assets that can’t be disrupted plus direct beneficiary status from the same AI wave disrupting everyone else.

HALO AI Defensive stocks are the physical-world businesses using AI as a productivity tool to run their existing operations more efficiently. 

• Walmart (WMT) is the canonical example. One of the world’s largest logistics networks, physical store operators, and grocery supply chains are now deploying AI to optimize demand forecasting, reduce inventory waste, and cut labor costs.
• Caterpillar (CAT) is deploying autonomous haul trucks in mining operations.
• FedEx (FDX) and UPS (UPS) are using AI route optimization to shave hundreds of millions off annual fuel and labor bills.
• Deere & Co. (DE) is embedding AI and autonomy into farm equipment so deeply that farmers are effectively locked in.
• Constellation rival Exxon (XOM) is using AI to optimize refinery operations and seismic reservoir analysis.

These stocks won’t have the explosive revenue ceilings of the offensive names. But they offer something arguably more valuable right now: genuine immunity from the AI disruption that is obliterating their pure-digital counterparts. 

When the market asks, “will this business still be here in five years?,” the answer for Walmart and Caterpillar and Eaton is an almost embarrassingly confident yes.

How to Position for the AI-Driven ÃÛÌÒ´«Ã½ Rotation

The HALO rotation isn’t a prediction or a thesis waiting for confirmation. 

It’s happening right now, denominated in real stock price moves, with real institutional dollars doing the moving. 

Energy is up 22% year-to-date. Materials are up 18%. Consumer staples are up 15%. The unglamorous XLE energy ETF is outperforming the Nasdaq by 25 percentage points so far this year. Caterpillar, Coca-Cola (KO), and Johnson & Johnson (JNJ) are all hitting record highs. Comfort Systems USA – a company that installs HVAC in buildings – is up 50%-plus. 

Meanwhile, the “Magnificent Seven” are all in the red for the year. Every single one. And the market speaks one language fluently: price action.

There is one major caveat worth stating directly: many of these stocks have already moved. Chasing a 50% run isn’t a strategy. The smarter play is finding HALO companies – particularly in the Offensive infrastructure layer and the Defensive industrial/materials categories – that haven’t yet been fully re-rated to reflect their AI-era positioning. 

There are dozens of them. The framework is the key; the specific names require homework.

The Bottom Line

The market isn’t flat. It just looks flat.

Underneath that calm surface, a generational rotation is underway, driven by a simple logic: AI is a digital tool. Digital businesses face disruption risk. Physical businesses largely don’t.

The companies selling the physical infrastructure that AI runs on are soaring. The companies operating physical-world businesses that AI can only improve – not replace – are holding up beautifully. 

The pure-play digital businesses in AI’s direct path are getting taken apart.

HALO – Hard Assets, Low Obsolescence – is the trade of 2026. And given the trajectory of AI capability, which shows no signs of slowing, it will likely remain the dominant investment framework for years to come.

The market has changed – and it isn’t going back to the old regime.

Retail capital moves faster. Technology accelerates cycles. Leadership doesn’t last for years anymore. Sometimes, it barely lasts for quarters.

In that environment, buy-and-hold on its own isn’t enough.

You need to flip volatility on its head – and trade momentum instead of fearing it.

My upgraded Nexus Stock Screener identifies fast-moving trades before they go parabolic. It’s the same framework institutional traders use to find the biggest winners; and now you can, too.

In back-testing, Nexus identified eight of 2025’s top-performing stocks before their major breakouts, including:

• Hycroft Mining (HYMC) before a 1,100% move.
• Terns Pharmaceuticals (TERN) before an 865% surge.
• MP Materials (MP) months before the Pentagon deal and Apple partnership sent it soaring.

If you’re going to position for the HALO era, you need more than a thesis. You need timing – because in this market, leadership changes fast, and hesitation gets expensive.

The old playbook is fading in real time. Capital is already rotating.

Watch my new presentation to see what’s replacing it – and how to position before the next breakout wave accelerates.

The post The ÃÛÌÒ´«Ã½ Isn’t Flat. It’s Rotating – And AI Is the Trigger appeared first on InvestorPlace.

If you look online at photographs from that era, you see bustling downtown cityscapes with modern cars and advertising. Bellbottom jeans and miniskirts. Women and men studying at university. People dancing. The country was modernizing rapidly, and its economy was becoming more integrated with the rest of the world.

That all changed in 1979.

The Islamic Revolution reshaped Iran’s political system, its relationship with the West and its role in global energy markets. Over time, tensions increased, sanctions followed and Iran became a recurring source of geopolitical risk.

Fast forward to today.

Negotiations between the U.S. and Iran reportedly broke down late last week. The U.S. and Israel initiated attacks over the weekend targeting Iran’s senior leadership as well as missile launchers, nuclear facilities and Islamic Revolutionary Guard Corps infrastructure. Iran retaliated with missile and drone strikes across the region. The U.S. has since closed embassies in Kuwait and Saudi Arabia and encouraged Americans to leave parts of the Middle East.

Source: Wikipedia

As expected, oil prices jumped and markets sank today as investors worried about the fallout.

In today’s ÃÛÌÒ´«Ã½ 360, I’ll explain what this Middle East escalation really means for the stock market, why U.S. equities are holding up better than global markets and how to position yourself as volatility unfolds.

The U.S. Remains the Oasis

Now, you can get the rundown on exactly what has transpired over the last couple of days anywhere. So, here is what has caught my attention amid all of this…

A few corners of the market have been spared during the recent uptick in volatility.

• The U.S. dollar staged its biggest rally in more than nine months.
• Gold prices surged back above $5,300 per ounce on Monday and remain just below all-time highs.
• West Texas Intermediate crude oil jumped above $75 per barrel, while Brent crude rose above $85 per barrel for the first time since July 2024.

Also, if you think it has been bad in the U.S. equity market this week, it looks like a picnic compared to the rest of the world.

According to Bespoke Investment Group, since the joint U.S.-Israeli strikes on Iran, the SPDR S&P 500 ETF (SPY), which tracks large U.S. stocks, has declined about 1.7% through early Tuesday trading. Meanwhile, the SPDR MSCI ACWI ex-U.S. ETF (CWI), which tracks developed and emerging market stocks outside the United States, has fallen roughly 6.8%.

That is a performance gap of more than five percentage points in just two trading sessions. That kind of performance gap has occurred only twice since CWI began trading in 2007.

The reason comes down to one word. Oil.

Crude prices have posted back-to-back daily gains of more than 6%, pushing them to 52-week highs. Most major economies remain heavily dependent on Middle Eastern oil. The U.S. economy, however, has become far more insulated over the past 10 to 15 years, thanks to our abundance of oil and natural gas in places like the Permian Basin in West Texas.

Think about it this way.

We export crude oil. We export liquefied natural gas. Much of the developed world does not.

That narrow passage in the image above handles roughly a quarter of global crude and a fifth of LNG exports. That is why international markets are under far greater pressure right now.

By contrast, higher prices create windfall profits for U.S. energy companies rather than crippling the broader economy.

Now, military action typically does not affect the stock market. If anything, it often removes a level of uncertainty in the market, and I think that will be the case this time around, too.

ÃÛÌÒ´«Ã½s do not like unknown outcomes. Once objectives become clear and the path forward is better defined, investors adjust.

For decades, Iran has been a persistent geopolitical risk, and that gets priced into oil, currencies and equities. If long-standing tensions ease and energy flows normalize, that removes a lot of uncertainty from the global system. And when that happens, markets have room to grow.

But here’s what matters.

The United States is food and energy independent.

We are one of the world’s dominant energy producers. Higher crude prices may even help narrow the trade deficit and support GDP growth. And a stronger dollar reinforces America’s position as a safe haven during global stress.

In other words, while this conflict creates pressure overseas, it does not hit the U.S. economy the same way.

That is why I continue to say the U.S. remains the oasis.

The Bigger Opportunity Ahead

Volatility is uncomfortable. I understand that.

But this is exactly when discipline matters most. I urge you to block out the noise and not let near-term events derail your focus on the big-picture, long-term themes that are far more important for building wealth.

In fact, while headlines focus on oil tankers and missile strikes, a far larger shift is already accelerating inside the U.S. economy.

Despite what the worrywarts in the media might say, I believe a new phase of the artificial intelligence revolution is unfolding.

And it is being driven by someone Yahoo Finance once called “one of the most hated people in the world.”

Elon Musk.

He revived the electric car industry. He revolutionized private space flight. He built the largest satellite network on Earth.

Now he is preparing to ignite what I am calling Project Apex.

This initiative is designed to accelerate the next stage of AI – powered by a shocking level of computing power and infrastructure buildout.

All with one singular goal. An inflection point for AI where we don’t look back, and nothing is the same again.

I do not say this lightly. My firm has already staked $358 million on this technological shift.

Why? Because this is one of the biggest moneymaking opportunities of the decade.

As capital floods into new data centers, chips, energy infrastructure and AI systems, a small group of companies stands to benefit disproportionately.

That’s why I recently released a full presentation explaining:

• How Elon Musk is preparing to spark this next chapter in the AI revolution
• Why I believe it could create the potential for dramatic upside as this next phase accelerates
• Details of the A-rated company at the center of it
• And how you can position yourself before Wall Street fully prices it in

I even tested Elon’s newest AI breakthrough myself and walked through it in a live demonstration.

Geopolitical volatility will come and go. But if you are serious about capitalizing on the next wave of the AI boom, you need to see this now.

Take the time to watch the full briefing today.

Sincerely,

Louis Navellier

Editor, ÃÛÌÒ´«Ã½ 360

The post While ÃÛÌÒ´«Ã½s Worry About Iran, Remember This… appeared first on InvestorPlace.

As I write on Tuesday afternoon, the market is staging a comeback.

Earlier today, fear gripped Wall Street due to escalating tensions in the Middle East.

All three major indexes were down more than 2% in a classic “sell first, ask questions later” session.

Gold was off 4%… silver had dropped nearly 8%… Bitcoin was lower… and just about everything – apart from oil – was being sold indiscriminately.

It was the kind of move where fear overrides analysis.

The primary driver of that early selloff was the risk we flagged in yesterday’s Digest – the potential closure of the Strait of Hormuz, a critical waterway responsible for roughly 20% of global oil trade.

An official from Iran’s Revolutionary Guards said Iran “will set fire to any ship attempting to pass through the Strait.” That headline sent energy prices higher and traders scrambling.

But just as we’re going to press, a major development hit the wires: President Trump announced the U.S. Navy will escort tankers through the Strait of Hormuz if necessary.

Here’s Trump from Truth Social:

If necessary, the United States Navy will begin escorting tankers through the Strait of Hormuz, as soon as possible.

No matter what, the United States will ensure the FREE FLOW of ENERGY to the WORLD.

That statement directly targets the market’s core fear: a sustained disruption to global oil supply.

The market reaction was swift. As I write near 3:00 p.m. Eastern, the Dow is down just 0.6%, the S&P 500 is off about 0.75%, and the Nasdaq is lower by 0.8%.

This intraday reversal tells us something critical: markets are still watching oil closely – but they are not yet pricing in a sustained, durable energy shock. More on that in a moment.

First, let’s back up and cover today’s events from the beginning. Here’s legendary investor Louis Navellier from his Growth Investor Flash Alert from earlier today:

The Republican Guard [Islamic Revolutionary Guard Corps (IRGC)] has said the Strait of Hormuz is closed now.

And everybody’s looking at alternative shipping routes because the insurance on any ship going through the Strait of Hormuz is cost prohibitive…

You have Brent crude at $84 and WTI (West Texas Intermediate) crude approaching $80. 

Global markets also reacted to Iran’s attacks on critical energy infrastructure in the Middle East. Iranian drones and/or ballistic missiles have hit Qatar, Saudi Arabia, the UAE, Kuwait, and Oman.

So, where does this conflict go from here – and what’s the appropriate response in your portfolio?

Three likely outcomes and their respective market impacts

To help us navigate how the Middle East conflict might play out, and what it means for the markets, let’s go to our hypergrowth expert Luke Lango, editor of Innovation Investor.

After assessing military developments, political signaling, market pricing, and prediction markets, Luke sees three potential paths forward.

Path A: Negotiated Resolution

In this possibility, talks between U.S. and Iranian officials prove successful, and we reach a ceasefire within weeks.

The scenario here: apply maximum pressure, force negotiations, declare victory, and step back.

The risk is the permanent closure of the Strait of Hormuz. Here’s Luke:

Even a temporary disruption can send energy prices sharply higher and ripple through inflation and growth forecasts.

But if negotiations and de-escalation are successful, Luke sees the conflict and the market impact resolving soon:

This would be the “nothing burger” scenario for the U.S. economy.

Assuming the Strait of Hormuz is reopened shortly, we’ll likely see the brief oil spike fade.

ÃÛÌÒ´«Ã½s will recover recent losses within days to weeks.

Path B: Revolutionary Guard Hardliner Consolidation/Prolonged Conflict

Iran’s regime was built to survive leadership decapitation. So, a Revolutionary Guard consolidation around a hardliner could mean publicly announced talks, but regional escalation.

Luke says that this hypothetical could include proxy activation (e.g., Hezbollah), tanker disruptions, and sustained pressure in the Persian Gulf.

Here’s Luke with how that could translate into markets:

Oil at $100 to $140 per barrel, European gas structurally elevated, and the AI trade bifurcates sharply:

• Defense AI – Palantir (PLTR), Booz Allen (BAH) – and cybersecurity AI – CrowdStrike (CRWD), Palo Alto (PANW) – surge.
• Commercial AI infrastructure faces pressure due to the risk of stagflation.

We end up with a meaningful, sustained sector rotation away from growth and toward energy and defense – painful, but not a market collapse.

Path C: State Collapse/Failed State

If orderly succession fails and factions compete for control, then Iran could slide into chaotic fragmentation. This would likely mean regional conflict spillover, nuclear security concerns, and uncontrolled proxy activity.

In that case, Luke says the investment fallout could be severe:

This is the scenario nobody has fully priced…

A genuine nightmare for nearly every asset class except gold (which targets $6,000/ounce-plus), hard assets, and domestic defense.

This is the scenario where oil heads to $150 to $200 per barrel, inflation reheats, the Federal Reserve hikes interest rates, and a genuine U.S. recession emerges.

A quick sidenote since Luke brought up gold…

Why is it selling off today? Isn’t it supposed to be a safe haven for wealth during chaotic markets?

Yes, but there’s an old saying on Wall Street…

In a crisis, correlations go to one.

When fear spikes, investors sell what they can – not just what they should. But that phase rarely lasts.

History shows that once panicked forced selling subsides, gold typically resumes its role as a volatility hedge.

Circling back to Louis, this is why he’s still bullish on the yellow metal:

Now, gold technically is down today, but gold stocks should be very, very resilient.

So, which of the potential outcomes is most likely?

No one knows.

Yesterday, the market was pricing in Path A. This morning’s selloff suggested traders were hedging against Path B.

But this afternoon’s rebound tells us something important: investors are not yet convinced this will become a sustained energy shock.

That doesn’t eliminate Path B or C going forward. But it reinforces the same variable we flagged yesterday…

The Strait of Hormuz and its impact on oil prices.

After all, whether you like it or not, oil remains the lifeblood of the global economy. It powers approximately 33% of global energy consumption, dominates transportation fuel, and is essential for the production of plastics, chemicals, and fertilizers.

So, if oil prices explode higher and remain there, that’s our red flag. And behind that risk is the Strait of Hormuz.

Here’s Luke making the same point:

Limited conflict that doesn’t permanently impair Hormuz transit is not a structural market threat…

Watch energy markets, not just the S&P 500, for the real-time risk barometer…

Goldman Sachs’ (GS) chief strategist put the key question correctly: The stock market’s reaction will hinge “less on headline risk and more on the durability of any energy shock.”

But this afternoon’s news from President Trump directly addresses the market’s core fear – a sustained disruption to global oil supply – and helps explain the sharp intraday rebound.

What to do in your own portfolio

Mornings like this are when investment plans earn their keep.

When markets are calm, it’s easy to talk about discipline. When everything is flashing red and oil is spiking, that discipline gets tested.

So, instead of trying to predict what Iran will do next, along with the ensuing fallout, let’s be wiser and ask a core question…

What kind of stocks do I actually own?

This is where the distinction I’ve highlighted before in the Digest becomes critical…

Do you own high-conviction investments or low-conviction trades?

Step 1: Separate your portfolio into two buckets

High-conviction holdings are your multi-year (or multi-decade) compounders.

You own them because of durable competitive advantages, structural tailwinds, and long-term earnings power.

You’ve already accepted that:

• They will fall in bear markets.
• They could drop 30%–40% at some point.
• But you’d still hold them.

So, your default here is to sail through this volatility. But for this to be the case, they must pass one test today…

Has the Middle East conflict permanently impaired your original thesis?

If the answer is “no,” then a 10%–20% pullback may be far less a threat, and far more an opportunity.

Limited geopolitical conflict does not invalidate long-term secular winners. If your thesis remains intact, lower prices just improve future returns.

So, revisit the reason you bought each of those stocks. If those reasons still stand, today’s volatility alone is not a sell signal.

Step 2: Treat speculations like speculations

Now let’s talk about the other bucket – low-conviction positions.

These are:

• Momentum trades
• Tactical plays
• Shorter-term opportunities
• Smaller positions because you weren’t fully committed

In these names, today’s fear-based price action matters.

If you entered them primarily to capture bullish momentum, and this sudden risk-off behavior has clearly broken that momentum, then conditions have changed.

So, if your stop-loss triggered, there’s no debate – the decision has already been made. After all, protecting capital during falling markets is how you make sure you have dry powder to put to work when confidence returns (along with more buyers).

And to Luke’s point, even though we all want Path A, if we get Path B or C, then many speculative trades will end up falling much lower.

Stepping back, the real danger to your portfolio todayisn’t volatility – it’s blurring the line between speculation and conviction.

Wrapping up

The market was chaotic this morning, but the rebound reminds us how quickly sentiment can shift.

And even if selling pressure returns, Luke’s more severe scenarios point to rotation and repricing – not the end of the investment landscape.

The Strait of Hormuz and oil prices will determine whether this becomes a brief shock or a more prolonged one. So, we’ll be keeping an eye on that with you.

But until there’s greater clarity there, your edge will come from executing your plan – the basic blocking and tackling of investing. That’s how you stay rational when markets aren’t – and how you compound your wealth through chaos.

We’ll keep you updated here in the Digest.

Have a good evening,

Jeff Remsburg

The post From Panic to Rebound – Today’s Rollercoaster appeared first on InvestorPlace.

On Saturday, Feb. 28, 2026, the United States and Israel launched a new military campaign against Iran: Operation Epic Fury. Now Iran’s Supreme Leader, Ayatollah Ali Khamenei is dead. Gulf states are intercepting Iranian missiles.

Take a breath…

We’ve been carefully tracking this situation since the first explosions were reported over Tehran. Here’s our assessment after 72 hours of rapid-fire geopolitical analysis.

ÃÛÌÒ´«Ã½s, so far, are signaling restraint rather than panic. Equities remain stable, volatility is elevated but controlled, and energy markets have not priced in a sustained supply shock. That suggests investors see escalation risk as real, but not existential.

From our vantage point, this episode does not automatically derail the broader equity rally or the AI-led capital cycle…  provided the conflict does not expand beyond its current theater.

In fact, select AI and defense-linked equities have outperformed in early trading, reflecting expectations of sustained investment in automation, cybersecurity, and military AI systems.

That said, we’re still inside the first 72 hours of a fluid situation. There’s a lot to unpack here, so let’s dive right in. 

What Happened In the U.S. Strike On Iran – And How It Compares to Previous Conflicts

The United States’ and Israel’s coordinated military operation struck targets across Tehran and other Iranian cities. The scope was stunning: a large joint package of Israeli aircraft and U.S. long-range strike assets, including B-2s, plus fighters and one-way attack drones. In the first 24 hours alone, U.S. officials say the campaign struck more than 1,000 targets.

The strategic result was equally stunning. Supreme Leader Ali Khamenei – the 86-year-old theocratic overlord who had ruled Iran for 36 years – was killed in the opening strikes. So were the commander of the Islamic Revolutionary Guard Corps (IRGC), the defense minister, the armed forces chief of staff, the Supreme National Security Council secretary, alongside multiple senior figures across Iran’s security leadership – in a single opening wave.

This has no modern precedent. We’ve seen decapitation strikes before but typically against single high-value targets, not a sweeping leadership hit. What just happened was the simultaneous removal of the entire top layer of a sovereign nation-state’s military and political leadership. It’s audacious, historically unprecedented, and – depending on what follows – either a masterstroke or a catastrophic miscalculation.

How does this compare to previous U.S. Middle East conflicts?

It is not Iraq in 2003. There aren’t 150,000 troops on the ground. There is no stated intention to occupy Iran. President Trump’s explicit framing – a “four-week process” designed to destroy Iran’s military capacity and create the conditions for the Iranian people to reshape their own government – is a fundamentally different doctrine than the Bush-era nation-building venture that consumed a decade, $2 trillion, and ended with… well, ISIS. 

It is not the Gulf War in 1991. That was a coalition of 35 nations responding to clear-cut territorial invasion, with broad international legitimacy and congressional authorization. Operation Epic Fury is a U.S.-Israel operation with virtually no international support. The European Union called for “maximum restraint.” Oman expressed “dismay.” And even within the U.S., only 1 in 4 Americans approve per early polling. The political staying power of an unpopular, congressionally unauthorized war has hard structural limits.

It most closely resembles what we saw in June 2025 – also a U.S.-Israel joint strike targeting Iranian nuclear facilities and military infrastructure – which lasted 12 days, produced an oil spike, and ended with a ceasefire that has largely held since. ÃÛÌÒ´«Ã½s sold off briefly at its onset, then recovered fully when it became clear the conflict was limited. 

The June 2025 playbook is what the smart money is running right now. The critical difference this time is scale and stated ambition. 

June 2025 targeted the nuclear program. February 2026 targets the regime itself. That escalation in objective is what makes this genuinely more dangerous and uncertain.

Operation Epic Fury: Three Likely Outcomes – And the ÃÛÌÒ´«Ã½ Impact

After tracking military developments, political signaling, market pricing, and prediction market data, here is our current read on the situation. 

We see three potential pathways forward. Fortunately, the best one – Path A – is the most likely. 

Path A: Managed Transition/Negotiated Resolution

This is the scenario the market is most clearly pricing.

Trump confirmed on Sunday that Iranian officials are already talking. “They want to talk, and I have agreed to talk,” he said. The surviving Iranian leadership, led by acting head of state President Masoud Pezeshkian (who ran for office on a platform of Western engagement), reached out for negotiations within 48 hours of Khamenei’s death. 

While prediction markets are uncertain and gameable, it’s worth noting that the odds at Polymarket currently favor a ceasefire by late April.

The strategic template here is the Jan. 3 capture of Venezuelan President Nicolás Maduro: maximum military pressure applied until the adversary’s rational self-interest calculus flips, then a deal is met, all parties declare victory, and everyone goes home. The administration is running the same play at a greater scale in Iran.

The central risk: The Strait of Hormuz has remained contested – with intermittent disruption and heightened war-risk conditions. As of this writing, Iran’s Islamic Revolutionary Guard Corps has effectively closed the Strait of Hormuz, telling vessels they will not be permitted to pass. Reopening Hormuz is a prerequisite for a ‘Path A’ outcome. The strait is a critical global oil chokepoint, carrying roughly one-fifth of all seaborne oil and natural gas flows from the Persian Gulf to world markets; even a temporary disruption can send energy prices sharply higher and ripple through inflation and growth forecasts. We’ll continue monitoring developments here closely. 

Investment implications: The “nothing burger” scenario for the U.S. economy. Assuming the Strait of Hormuz is reopened shortly, we’ll likely see the brief oil spike fade. ÃÛÌÒ´«Ã½s will recover recent losses within days to weeks. The AI bull market – interrupted but not impaired – will resume with full force. The lasting structural effect is a rerating of defense AI, cybersecurity, and AI energy infrastructure names that benefit regardless of how the conflict resolves.

Path B: Revolutionary Guard Hardliner Consolidation/Prolonged Conflict

Iran’s Islamic Republic regime was specifically designed to survive decapitation. Its overlapping institutional architecture was built after 1979 precisely so no single strike could topple it. 

Before Operation Epic Fury launched, the CIA assessed that Khamenei’s death would most likely produce Revolutionary Guard hardliner consolidation rather than regime collapse. That assessment hasn’t been invalidated; it’s been complicated.

Iran could simultaneously agree to talks with America and Israel while activating Hezbollah in Lebanon, striking U.S. tankers in the Persian Gulf, and using the mourning period to rally nationalist sentiment. 

Investment implications: The prolonged conflict scenario. Oil at $100 to $140 per barrel, European gas structurally elevated, and Hezbollah opening a full northern front, stretching U.S. military resources across two theaters. 

The AI trade bifurcates sharply: 

• Defense AI – Palantir (PLTR), Booz Allen (BAH) – and cybersecurity AI – CrowdStrike (CRWD), Palo Alto (PANW) – surge.
• Commercial AI infrastructure faces pressure due to the risk of stagflation. 

We end up with a meaningful, sustained sector rotation away from growth and toward energy and defense – painful, but not a market collapse.

Path C: State Collapse/Failed State

This is the scenario nobody has fully priced. 

The simultaneous killing of Iran’s entire top military command doesn’t just decapitate the regime; it may prevent clean succession. Multiple IRGC factions, clerical factions, and opposition movements could compete for power simultaneously, with no single actor strong enough to impose order. The result: geopolitical chaos, ungoverned nuclear materials, autonomous proxy networks, and regional powers scrambling to fill the vacuum.

Investment implications: A genuine nightmare for nearly every asset class except gold (which targets $6,000/ounce-plus), hard assets, and domestic defense. This is the scenario where oil heads to $150 to $200 per barrel, inflation reheats, the Federal Reserve hikes interest rates, and a genuine U.S. recession emerges. The AI trade doesn’t die – it transforms entirely into a national security story – but the timeline extends by years, and the path forward is extraordinarily painful. Fortunately, this is the least probable of the three likeliest outcomes.

How Oil, Gas, and Stocks Reacted to the U.S. Strike On Iran

The mild price action yesterday was not investor complacency but calibration.

On Monday, March 1, stocks initially sold off on the open – then clawed back a meaningful portion of the move as investors treated the conflict as limited rather than systemic. 

That is not “World War III” price action – because the market doesn’t think this is World War III. It is pricing Path A at roughly 55% to 65% probability. Prediction markets with half a billion dollars in real money on the line confirm this read. 

Goldman Sachs‘ (GS) chief strategist put the key question correctly: The stock market’s reaction will hinge “less on headline risk and more on the durability of any energy shock.” A limited conflict that doesn’t permanently impair Hormuz transit is not a structural market threat. June 2025 showed that. The market is correctly treating it as the base case until evidence changes.

Our assessment is largely in agreement with current market pricing. As of now, the mild reaction is appropriate, not naive.

However, there is one important development worth flagging: While stock markets are calm, European natural gas prices have surged 50% after Qatar halted liquefied natural gas (LNG) production following Iranian attacks on its facilities – a magnitude of energy disruption that most investors are underweighting. 

Watch energy markets, not just the S&P 500, for the real-time risk barometer.

What to Watch: Green Lights and Red Flags

On the positive side of the ledger, here’s what we are watching for that would indicate we are heading toward a peaceful, diplomatic resolution to this conflict: 

• Pezeshkian or senior Iranian officials making any public language gesturing toward negotiation, even obliquely. 
• China announcing diplomatic mediation, as Beijing’s oil supply depends on the Strait of Hormuz, and they have the most leverage of any external actor to broker a deal.
• Documented Revolutionary Guard defections, even a handful of senior commanders seeking immunity. 
• The Hormuz remaining functionally open for tanker traffic.
• A second confirmed round of back-channel talks through Oman or another mediator.

Progress on any of these fronts would be a positive development for the stock market. 

Meanwhile, on the flip side of this coin, here are the potential red flags we’re watching that could derail our thesis:

• Physical Hormuz closure lasting more than 72 hours – the oil market nuclear option and the single most important variable to monitor daily. 
• Confirmed serious damage to a U.S. vessel – especially a carrier or large-deck platform. (Iran will claim big hits; confirmation is what matters.)
• Hezbollah escalating to a full-scale rocket campaign from Lebanon. 
• Pezeshkian being sidelined by a named IRGC hardliner. 
• Oil moving sustainably above $100 per barrel. 

None of these have yet occurred, but they are the signposts on the road to Path B or Path C, and they warrant daily monitoring.

AI in Operation Epic Fury: How the U.S. Strike On Iran Was Powered by Tech

Now, here’s a crucial detail that’s been buried beneath the chaotic headlines of the past few days.

Reporting over the past few days indicates U.S. Central Command leaned on Anthropic‘s Claude during Operation Epic Fury as an intelligence and decision-support tool – helping analysts sift signals faster, spot patterns, and pressure-test operational scenarios in real time. The precise scope of Claude’s role hasn’t been fully laid out publicly, but the strategic signal is unmistakable: Frontier AI is being operationalized inside the U.S. national security stack.

The irony abounds: On Friday afternoon, Trump ordered federal agencies to phase out Anthropic. Then, the military reportedly leaned on Claude in the biggest operation of the year. Washington can’t even keep its own AI story straight.

But set the political theater aside, and look to the strategic signal. 

Artificial intelligence has just demonstrated that it is not merely a corporate productivity tool. It is a national security weapon – and a decisive one. 

The same technology helping your marketing team write copy and your developers ship code faster was just used to process petabytes of satellite imagery and signals intelligence to locate one of the most heavily guarded humans on Earth.

The “AI agentic inflection point” we’ve been writing about for months just went public in the most dramatic fashion imaginable. AI isn’t coming to national security. It’s already there, deeply integrated

It’s so embedded that even a presidential phase-out order with a six-month timeline won’t unwind it overnight – and it’s about to attract an enormous new wave of government funding that has nothing to do with corporate capex cycles.

The defense-AI convergence has just been validated in real time. Palantir, Booz Allen, and the AI infrastructure companies supplying compute and models for military applications are not speculative plays. They are embedded in the operational backbone of the world’s most powerful military.

Our Bottom Line: The Game Plan Doesn’t Change

The global chessboard has changed significantly. 

A 36-year theocratic regime has been decapitated. The Middle East order is in genuine flux. The world’s most important oil shipping lane is threatened.

But from the perspective of the U.S. stock market? Not much has changed yet, and most likely, it won’t.

The doomsday scenarios – $100-plus oil, more inflation, delayed rate cuts, a prolonged armed conflict, a genuine U.S. recession – remain low-probability possibilities. 

Of course, those risks are real, as we’ve outlined above. But they are not the base case, and managing a portfolio entirely around tail risks is how you miss every bull market.

Our core bull thesis for 2026 has not changed. It has been reinforced.

We entered this year pounding the table on our “Acquisition Americana” bull thesis. We told folks to own oil and gas, defense names, and hard assets (gold, silver, and platinum) as America ditched its “global police” positioning in favor of a new imperialist era. 

Hopefully, many people listened. Those trades have been on fire since January 1 – and they just received further validation.

But more importantly, our central conviction – the AI bull market – has just received its most unexpected and most powerful validation yet. The same GPU clusters, foundational models, and AI infrastructure buildout we’ve been invested in for 18 months just played a starring role in the most consequential military operation in a generation. 

The AI trade was already inevitable. It just became undeniable.

Any war will pass. But the AI Revolution won’t.

Stay focused where it matters.

What we just witnessed wasn’t just military innovation. It was the public debut of AI as a sovereign capability.

And when the company most synonymous with that capability – OpenAI – enters public markets this year, investors won’t be buying an app. They’ll be buying the backbone of a new technological order.

The biggest gains in every platform shift go to investors who position themselves before Wall Street fully wakes up.

I’ve identified a way to gain exposure ahead of OpenAI’s IPO – before the headlines, before the S&P inclusion, before the frenzy.

If you’re going to stay focused where it matters, this is where to start.

The post U.S. Strike on Iran: What Operation Epic Fury Means for ÃÛÌÒ´«Ã½s appeared first on InvestorPlace.

Now, I should mention that my recent episode of Navellier ÃÛÌÒ´«Ã½ Buzz was filmed before the attacks occurred, so I would be remiss if I didn’t acknowledge what happened.

But I will say it is clearly designed to change the ruling regime as well as be fast and furious, and hopefully we’ll learn the results early next week. Normally, military actions don’t impact the stock market – if anything, this might help, because it removes uncertainty.

But there are three obvious beneficiaries to this action: the dollar, energy stocks and also gold stocks.

I’ll share more of my thoughts on it this week.

In other news, NVIDIA Corporation’s (NVDA) earnings last week served as the grand finale to earnings season. The company reported 73% earnings growth, 82% operating income growth and gave a positive outlook for the future.

But it didn’t rally. It fell 5% the next day.

So, what happened?

I explained what I think was going on in this week’s Navellier ÃÛÌÒ´«Ã½ Buzz, and why I think it’s considered a buy on any dip. I also discussed how mortgage rates have dropped below 6%, how the 10-year Treasury yield is near the lowest level in three years and what that means for interest rates and stocks.

Click the image below to watch now.

To see more of my videos, click here to subscribe to my YouTube channel.

Plus, the grades in Stock Grader (subscription required) have been updated this week! Click here to plug in your own stocks and see how they rate.

The Next Phase of AI Is Just Beginning

NVIDIA’s results made one thing clear: AI demand is still growing at a breakneck pace.

But I believe a much bigger shift is starting to take shape.

The world’s top tech leaders are racing to unlock the next stage of AI.

Data centers are expanding. Energy demand is rising. And billions of dollars are pouring into this buildout.

That’s why I’ve committed $358 million of my firm’s capital to this next stage of the AI boom.

I don’t make moves like this lightly. This next phase could unfold faster than most investors expect.

In a special presentation, I explain what’s driving this new chapter in AI, why this shift could create major opportunities and how you can position yourself now.

Plus, I’ll tell you about a company at the center of it all.

If you want to understand where AI is headed next, I encourage you to watch this presentation now.

Sincerely,

Louis Navellier

Editor, ÃÛÌÒ´«Ã½ 360

The Editor hereby discloses that as of the date of this email, the Editor, directly or indirectly, owns the following securities that are the subject of the commentary, analysis, opinions, advice, or recommendations in, or which are otherwise mentioned in, the essay set forth below:

NVIDIA Corporation (NVDA)

The post NVDA Beats by 73%… Why Did It Drop? Plus, Mortgage Rates Hit Lowest Level in Three Years appeared first on InvestorPlace.

Over the weekend, the United States and Israel launched large-scale strikes on Iranian military and leadership targets.

Early reports confirm that Iran’s Supreme Leader, Ayatollah Ali Khamenei, was killed in the opening wave. Multiple senior commanders were also killed.

Iran has begun to retaliate. Missile and drone attacks have targeted Israeli positions and U.S. assets across the region. Explosions have been reported near key Gulf installations, and the U.S. has confirmed American casualties. Civilian casualties have also been reported across the region.

Meanwhile, Iran has moved to restrict traffic through the Strait of Hormuz – one of the world’s most important oil chokepoints.

This is not a symbolic flare-up. This is a major escalation with enormous geopolitical and economic implications.

Let’s walk through the investment markets to assess the response.

Could oil go to $100?

As I write Monday mid-morning, U.S. West Texas Intermediate Crude (WTIC) trades at roughly $71.00 – a 6% jump from Friday’s close of $67.02.

The higher price reflects fear that the conflict could escalate, leading to a major supply shortage. The biggest risk in this scenario is that Iran shuts down the Strait of Hormuz – roughly 20% of global oil supply moves through it.

Even the threat of a complete Iranian blockage changes the economic calculus. Insurance costs rise. Shipping reroutes. Risk premiums expand. Traders hedge.

So, markets are now pricing in the possibility that this becomes more than a headline spike. Here’s CNBC:

Tanker traffic through the Strait has already effectively come to a halt as shipping companies take precautionary measures, according to consulting firm Rystad Energy…

The worst-case scenario is an attack by Iran on Saudi oil infrastructure followed by a complete closure of the Strait, [Andy Lipow president of Lipow Oil Associates] said Sunday.

Oil prices would jump by $10 to $20 in this scenario.

Oil market commentators warn that a prolonged blockade could send prices soaring beyond $120–$130 per barrel.

How to play oil today

To capture any additional spikes in crude prices directly, the United States Oil Fund (USO) is the most common tool. It tracks oil futures, so it moves in concert with the actual price of a barrel of WTIC. It’s up just over 6% as I write.

However, because the fund constantly “rolls” these contracts into the next month, it can be a leaky bucket for long-term holders due to maintenance costs known as contango. I won’t get into the mechanics of this now, but it’s important to view USO more as a short-term trading vehicle, not a long-term buy-and-hold play.

A steadier alternative is the Energy Select Sector SPDR (XLE), which invests in integrated giants like ExxonMobil (XOM) and ConocoPhillips (COP). These companies own everything from the wells to the gas stations, offering a safety net through steady dividends and refining businesses that can profit even when drilling is tough. It’s up about 2% today.

Finally, if you want a narrower bet on the companies doing the digging, the SPDR S&P Oil & Gas Exploration & Production ETF (XOP) focuses on “pure-play” drillers. These smaller, more aggressive companies often skyrocket when oil prices jump – it’s up more than 3% as I write – but they are far more volatile and can struggle if the market suddenly cools.

Overall, oil trades on fear faster than just about any other asset class – and right now, fear is back in the equation.

Will gold prices reach all-time highs?

When geopolitical risk rises, investors wanting stability turn to gold. That’s happening again today as the yellow metal once again reminds investors why it functions as a portfolio hedge during geopolitical instability.

As I write, gold is up about 2%, trading at about $5,343. But even higher prices could be on the way.

Some analysts suggest gold will soon retest its January 2026 record high of almost $5,600 per ounce. Some major banks, such as JPMorgan, are forecasting $6,300 if the regional conflict leads to a prolonged disruption of global trade.

For Wall Street, this move isn’t just about speculation – it’s pricing in the high stakes of a potential energy crisis and the resulting inflationary pressure.

The simplest way to position yourself for higher gold prices is through a gold ETF likethe SPDR Gold Trust (GLD) or the iShares Gold Trust (IAU). These funds are designed to track the price of gold bullion directly.

For a more concentrated bet, look to high-quality gold miners. Legendary investor Louis Navellier has been loading up his portfolios with quality miners for months.

Louis holds Agnico Eagle Mines (AEM) in the Growth Investor portfolio. Subscribers are up 212% as I write. And if you think it can’t keep climbing, here’s Louis from last week, pointing toward expected earnings growth – the driver of higher prices:

For its fiscal year 2025, Agnico Eagle Mines reported earnings of $8.28 per share, up 95.7% from the prior year.

Looking ahead to the first quarter in fiscal year 2026, the analyst community expects earnings to jump 119.6% year-over-year to $3.36 per share and for revenue to increase 66% year-over-year to $4.1 billion. 

Louis says AEM is a buy up to $268, so you still have time to get in. To join him in Growth Investor and access his other gold miners, click here to learn more.

Now, energy and gold are defensive reactions. But there’s also an offensive play that investors shouldn’t ignore.

Another high-octane option – drones

Modern warfare increasingly favors systems that are cheaper, scalable, expendable – and capable of operating without risking pilots.  

This puts drones in the spotlight.

This won’t surprise regular Digest readers. In our February 24 Digest, I wrote about how drones are transforming modern conflict. I quoted veteran trader Jonathan Rose, editor of Masters in Trading Live, who put it plainly:

Drones are no longer optional in modern defense.

They are becoming foundational technology, reshaping how conflicts are fought and how governments allocate capital.

Jonathan highlighted a handful of ways to play drones, but the company that has delivered some of the greatest returns for him and his subscribers over the last year has been Kratos Defense and Security Solutions (KTOS). 

It turns out, this is the exact name that our technology expert Luke Lango, editor of Innovation Investor, highlighted just before news of the attack on Iran:

Kratos (KTOS) is a leader in high-performance drones designed to be expendable. In a high-tempo environment, these systems get burned through like AA batteries.

That’s the difference between program defense stocks and op-tempo stocks.

If headlines read “U.S. Drones Strike Cartel Convoy,” legacy primes may move 1%.

High-beta drone manufacturers could move 10% to 15%.

Sure enough, as I write Monday, KTOS is up more than 10% – exactly as Luke described.

The bigger defense tailwind

This weekend didn’t create a defense boom – it just accelerated one that was already underway.

As Brian Hunt recently noted in his free newsletter Money & Megatrends, global defense spending is on pace to reach $2.6 trillion in 2026 – an 8% year-over-year increase.

Large-cap stocks like Lockheed Martin (LMT) and Northrop Grumman (NOC) have already been strong performers as defense spending accelerates. But Brian says that investors who focus purely on the big players are missing an enormous opportunity in smaller defense stocks:

Your average small cap aerospace and defense firm does not make the front of the Wall Street Journal. CNBC does not cover its quarterly earnings announcements.

However, this type of firm supplies critical components that the defense industry cannot function without. Flight control systems. Missile guidance system components. Rugged communications and surveillance gear for soldiers. Aircraft carrier parts.

As the defense industry booms, these small but critical players could see their market values rise by hundreds of percent.

Brian flags several smaller players – one that relates to drones is Innovative Aero (ISSC). Here’s Brian with more details:

ISSC is a $400 million company that supplies key systems like displays, sensors, navigation tools, and flight controls for military aircraft.

It is modernizing the cockpit by taking old military planes, and turning them into high tech, digital flight decks…

ISSC a one-stop shop for turning military planes into semi-autonomous drones

As I write Monday, ISSC is up 7% while LMT and NOC are up 3% and 4%, respectively – validating Brian’s point that smaller supply chain players often move much more than the headline names.

What we’re watching now

Historically, markets react immediately to geopolitical shocks, but soon thereafter begin asking the more practical question…

Is this a real supply disruption event or just a headline event?

If the Strait of Hormuz remains meaningfully restricted – not for hours, but for weeks – the story stops being about geopolitics and starts being about inflation.

While oil above $100 will boost energy stocks, it will tighten financial conditions, pressure margins, hurt Main Street budgets, and complicate the Federal Reserve’s path forward.

On the other hand, if this settles into contained retaliation – strikes without sustained energy disruption – then oil likely finds a ceiling, gold gives back some of its fear premium, and equities revert to trading earnings and liquidity.

So, we’re watching the Strait of Hormuz closely. What happens there will ultimately determine whether this is a temporary sector rotation or a sustained macro event with longer-term portfolio implications.

We’ll keep tracking it with you here in the Digest.

Have a good evening,

Jeff Remsburg

Disclaimer: I own GLD

The post Where Wall Street Turns as War With Iran Escalates appeared first on InvestorPlace.

Here are the seven questions that matter most right now.

1. Why Did Moderna Stock Crash So Hard?

The short answer: the fundamentals collapsed right along with the stock. Revenue fell by roughly 90% from pandemic highs, and Wall Street revalued Moderna accordingly — from hypergrowth vaccine winner to shrinking biotech.

The longer answer is more nuanced, and it’s where the opportunity starts to take shape.

Get the full collapse analysis for Moderna stock. →

2. Is Moderna Still Just a “COVID Company”?

That’s how the market is pricing it. But COVID-19 was never the business model — it was proof of concept for Moderna’s mRNA platform. The company has since built a late-stage pipeline that spans oncology, respiratory disease, and rare genetic conditions.

Whether that pipeline changes the valuation math is the central debate.

Read why the “COVID company” narrative misses the point for MRNA. →

3. How Important Is the Cancer Vaccine for Moderna Stock?

It may be the most important clinical program in biotech right now. Early data from Moderna’s personalized cancer vaccine — developed with Merck — showed a dramatic reduction in recurrence rates that caught the attention of oncologists and investors alike.

Multiple Phase 3 readouts are on the calendar. If the data holds up, the investment thesis shifts entirely.

See why the cancer vaccine is central to the Moderna stock bull case. →

4. Does Moderna Have Enough Cash to Fund Its Pipeline?

More than most investors realize. Strip out the net cash on Moderna’s balance sheet from the current share price, and you’re paying a surprisingly low amount for the entire pipeline.

The math here is one of the most compelling — and overlooked — parts of the Moderna stock story.

Review the cash runway analysis for Moderna stock. →

5. What Are the Biggest Risks for Moderna Stock?

They’re real and worth taking seriously. Structural revenue decline, regulatory headwinds from the current administration, and the ever-present risk that Phase 3 oncology data disappoints — any of these could extend the pain for Moderna stock.

See the full risk breakdown for Moderna stock before making a decision. →

6. What’s the Upside Target for MRNA Stock if the Cancer Data Delivers?

A move toward $100 per share is plausible — nearly double today’s price — if Moderna stock gets revalued as an oncology platform rather than a fading pandemic name. That outcome hinges on Phase 3 data and longer-term revenue visibility, but the global cancer immunotherapy market is large enough that even a small share would dwarf Moderna’s current revenue base.

See the valuation framework and upside scenario for MRNA. →

7. Is Moderna Stock a Buy Right Now?

At around $53, Moderna remains nearly 90% below its peak. Short term, the stock will move on clinical headlines. Long term, it comes down to one question: can the oncology platform deliver?

The complete risk-reward breakdown — including where I stand on whether MRNA belongs in your portfolio today — is in the full analysis.

Get the complete Moderna stock turnaround thesis. →

Thomas Yeung is a market analyst and portfolio manager of the Omnia Portfolio, the highest-tier subscription at InvestorPlace. He is the former editor of Tom Yeung’s Profit & Protection, a free e-letter about investing to profit in good times and protecting gains during the bad.

The post Moderna Stock (MRNA): Is It a Buy Now? 7 Questions After the Crash appeared first on InvestorPlace.

Last month, I posed a challenge…

Adjust your investing habit and look beyond U.S. markets.

Today, I’d like to check in.

Let’s start with a brief tour of the home front. Navigating our frenetic stock market during the several weeks has not been an easy task. On one hand, the market is lavishing gains on select companies, but also swiftly and severely punishing others.

It feels a bit like living with a pet lion. Sure, it can be cuddly and docile, but it can also maul you… even when it’s just playing, and especially if you scratch its tummy.

Precious metals, base metals, energy, and a select “AI-Applier” companies have remained on the lion’s good side. But the lion extended a paw and took a swipe at software stocks during the recent “SaaSpocolypse,” and the sector is still nursing its wounds. 

To be clear, I’m by no means bearish on the United States. I think we’re still the ground zero of innovation and capitalistic dynamism. But that doesn’t mean there aren’t other opportunities in other countries…especially when so many foreign stocks are sporting valuations that are substantially below their U.S. counterparts.

When I first posed the challenge to look overseas, I mentioned that monitoring other countries’ behaviors and what they’re doing with their capital allows you to expand your opportunistic reach.

Right now, global markets are under pressure due to higher geopolitical risk following this weekend’s events between the United States and Iran. That means we might see an increase in volatility for U.S. stocks in the near term, especially in broad market indices. Foreign markets may see the same fate, as global investors move to become more risk averse.

However, there is still a case to be made for the benefits of diversification. As I stated in my initial challenge: Over the span of a full market cycle, a dose of international exposure can provide a helpful diversification to your portfolio, while also growing your wealth.

Spreading investments internationally reduces reliance on the U.S. alone and can smooth overall returns over time. And some markets outside the U.S. may offer cheaper valuations.

Long-term investors – especially those focused on diversification – often benefit from foreign stocks over time, even through geopolitical turbulence.

One of the easiest ways to diversify into foreign stocks in uncertain times is by investing in an Exchange-Traded Fund (ETF) that holds a basket of foreign stocks. ETFs like these sometimes focus narrowly on a specific country, like the iShares MSCI Brazil ETF (EWZ). Others paint with a broader brush. The iShares MSCI Eurozone ETF (EZU), for example, holds a portfolio of stocks from across Europe..

ETFs give you diversified exposure across countries and sectors without betting on one region or stock. It’s instant diversification at a lower cost.

At Fry’s Investment Report, I have recommended foreign ETFs like EWZ that are currently capturing double-digit gains and outpacing the S&P 500 by a wide margin. While that benchmark U.S. index is hovering around break-even for the year-to-date, EWZ has soared more than 20%.

To learn more about my diversification strategy at Fry’s Investment Report, click here.

Now, let’s take a look back at what we covered here at Smart Money. Then, I’ll share what you can expect next.

Smart Money Roundup

ÃÛÌÒ´«Ã½s Move on Belief – Not Facts

February 25, 2026

In Wednesday’s issue, veteran trader Jonathan Rose argues that markets move on shifting expectations, not just headlines. He explains how prediction markets like Kalshi and Polymarket reveal real-money probability signals before prices adjust – and how smart traders can use these shifts in beliefs to position their portfolios. To read more about how to get ahead of major moves, click here.

How to Invest Smartly When the ÃÛÌÒ´«Ã½ Loses Its Mind

February 26, 2026

Drawing lessons from the April 2025 selloff and other historic volatile market moments, this issue explores why investors must stay calm in order to build a winning portfolio. Additionally, I explain why I recommend shifting toward domestically focused U.S. companies and foreign firms that operate solely on their home turf. Click here for more details.

The $110 Billion Bet on Super AI – and the Moves to Make Now

February 28, 2026

Last week, OpenAI secured a record-breaking $110 billion funding round, with Amazon, SoftBank, and Nvidia among the major backers racing to achieve artificial general intelligence (AGI). However, rather than chasing well-known AI names, I recommend investors follow a three-pronged portfolio strategy to position ahead of the crowd. Click here to read more about my approach.

Nvidia’s Earnings Signal a Shift in AI Expectations

March 1, 2026

Last week, Nvidia posted a blowout quarter with 73% revenue growth, yet shares still dipped as sky-high expectations proved to be nearly impossible to satisfy. Wall Street legend Louis Navellier warns that this signals an “AI Dislocation” – a shift in market leadership toward overlooked enablers like power, cooling, and networking companies. To learn about Stage 1 and Stage 2 stocks, and the specific companies Louis is eyeing, click here.

Looking Ahead

As volatility and uncertainty become the new normal, my InvestorPlace colleague Luke Lango has a new playbook:

Flip volatility on its head… and embrace momentum trading.

While I will continue to sing the praises of value investing, Luke offers a different insight with valuable information. This strategy can allow you to move quickly in and out of stocks as they gain and lose momentum.

And to help folks employ this playbook, Luke is gearing up to launch a brand-new screener that he and members alike can use to detect “breakout socks” in advance.

He will be joining us in your next Smart Money to share more about this trading strategy and his new screener tool. So, be sure to keep an eye out in your inbox.

Regards,

Eric Fry

The post As Volatility Flares Up Again, Strengthen Your Portfolio appeared first on InvestorPlace.

1. What Caused the CoreWeave Stock Collapse?

Wall Street got caught flat-footed. Margins deteriorated sharply across the board, and forward guidance came in well below expectations. Most alarming: CoreWeave plans to deploy $2.60 in capital for every dollar of revenue it expects to generate in 2026 — a ratio far above what analysts had modeled.

The market’s verdict was swift and severe.

Get the complete earnings breakdown and what it means for your portfolio.→

2. Did Anyone See This Coming?

I did — and the signal I saw came from inside the company.

Before the earnings report landed, CoreWeave’s own executives were quietly unloading shares at a pace that raised serious red flags. Senior officers sold millions of shares, many within days of receiving them. That kind of urgency from insiders rarely signals confidence.

Find out what CoreWeave insiders were doing before the crash — and what it may signal next.→

3. Is CoreWeave Actually a Tech Company?

Not in the way most investors think.

Strip away the AI branding and CoreWeave’s business looks more like a leveraged leasing operation than a technology firm. It raises capital, acquires hardware, rents it out, and uses the proceeds to service its debt. The margins of a lender. The debt load of a lender. And unlike true software businesses, it doesn’t get more efficient as it grows.

Understand why CoreWeave’s business model may be fundamentally misunderstood by the market.→

4. How Exposed Is CoreWeave to Losing Key Customers?

Extremely. Two customers account for more than three-quarters of the company’s revenue. That kind of dependence doesn’t just create risk — it eliminates pricing power entirely.

Management acknowledged during its most recent earnings call that rates for AI computing capacity failed to rise in 2025, even as demand accelerated. With operating margins forecast to shrink further in 2026, the revenue base is both concentrated and under pressure.

Read why CoreWeave’s customer concentration may be its most underappreciated risk.→

5. What Is CRWV Stock Actually Worth Right Now?

At current prices, the risk-reward math is difficult to justify.

A rigorous fundamental analysis puts my fair value estimate around $100 per share — close to where shares traded before the selloff. But for investors seeking adequate compensation for the company’s debt burden and business risks, the right entry point is materially lower than that.

Could momentum and retail enthusiasm push shares higher anyway? Absolutely. But there’s a difference between a trade and an investment.

See the full valuation framework and what price makes CRWV worth the risk.→

6. Why Am I Calling CoreWeave the Next MARA?

Because I’ve seen this movie before.

MARA Holdings was supposed to deliver leveraged exposure to bitcoin’s rise. Instead, the stock dramatically underperformed the underlying asset — weighed down by the same forces now bearing on CoreWeave: commoditized output, relentless capital requirements, and no durable competitive advantage. The parallel isn’t flattering.

Read the full MARA comparison and why it may be the most important lesson for CoreWeave investors.→

7. Where Should AI Bulls Put Their Money Instead?

The long-term case for AI investing remains compelling. The question is whether CoreWeave is the right vehicle.

Companies with proprietary software, defensible technology moats, and self-funding business models offer a very different risk profile — one that doesn’t depend on perpetual debt financing to stay competitive. Two specific names are already on my radar.

Discover which AI stocks may offer better risk-adjusted returns than CoreWeave right now.→

Thomas Yeung is a market analyst and portfolio manager of the Omnia Portfolio, the highest-tier subscription at InvestorPlace. He is the former editor of Tom Yeung’s Profit & Protection, a free e-letter about investing to profit in good times and protecting gains during the bad.

The post CoreWeave Stock: 7 Critical Questions Every Investor Should Ask Before Buying the CRWV Dip appeared first on InvestorPlace.

This Week’s Ratings Changes:

Upgraded: Strong to Very Strong

Downgraded: Very Strong to Strong

Upgraded: Neutral to Strong

Downgraded: Strong to Neutral

Upgraded: Weak to Neutral

Downgraded: Neutral to Weak

Upgraded: Very Weak to Weak

Downgraded: Weak to Very Weak

To stay on top of my latest stock ratings, plug your holdings into Stock Grader, my proprietary stock screening tool. But, you must be a subscriber to one of my premium services.

To learn more about my premium service, Growth Investor, and get my latest picks, go here. Or, if you are a member of one of my premium services, you can go here to get started.

Sincerely,

Louis Navellier

Editor, ÃÛÌÒ´«Ã½ 360

The post Alphabet Upgraded, United Airlines Downgraded: Updated Rankings on Top Blue-Chip Stocks appeared first on InvestorPlace.

There was a time when the government’s idea of “market involvement” was holding a hearing, not a portfolio.

But that was before the Genesis Mission.

Today, Uncle Sam is doing something extraordinary – and a little unnerving. He’s acting like the biggest activist investor on Earth, moving billions not with policy memos but with purchase orders.

And if you’re not watching what Washington is buying, you’re already behind.

Over the past few months, the federal government has taken equity stakes in four specific public companies: MP Materials (MP), Intel (INTC), Trilogy Metals (TMQ), and Lithium Americas (LAC).

And the market reaction has been explosive.

• MP Materials soared 50% in a single day after the Pentagon bought a stake.
• Lithium Americas doubled overnight, jumping 100% when the Department of Energy bought in.
• Trilogy Metals didn’t just double; it tripled overnight after the government wrote the check.

And White House officials have already said they intend to keep the cash flowing.

In other words, the most powerful buyer on Earth is repricing strategic national assets at will – creating mouthwatering investment opportunities for traders who know where to look. 

If you want to make the most of your time on Wall Street, you’ve got to be positioned in the stocks on the government’s shopping list. 

Because this is the “President’s ÃÛÌÒ´«Ã½.” And frankly, it’s going to make the AI bubble look like a warm-up act…

Why the Federal Government Is Now Picking Stocks

So, why is the government suddenly acting like a desperate venture capitalist? Because America is staring down what could be an ‘economic Pearl Harbor.’

For decades, America has been asleep at the wheel while China systematically captured the raw materials and supply chains that power the 21st century.

Take a look at your smartphone. Without a rare earth mineral called dysprosium, it’s little more than a paperweight. The same goes for your computer, electric vehicle, and the wind turbines and nuclear reactors that power them. Perhaps most importantly, without dysprosium, the U.S. military’s F-35 fighter jets don’t get off the ground.

Yet, China controls:

• Roughly 99% of the dysprosium supply.
• Nearly 90% of the active pharmaceutical ingredients for our drugs (antibiotics, heart meds, you name it).
• 96% of the processing for all rare earth minerals globally.

In 1992, China’s former paramount leader, Deng Xiaoping, famously said, “The Middle East has oil, China has rare earths.”

He knew that if China controlled the inputs, it owned the output. And now, the nation has us in a chokehold. 

Beijing has the power to turn off the lights on the American economy tomorrow if it wants.

Mines to Magnets: How Federal Investment Is Rebuilding U.S. Supply Chains

The White House knows this. And that is why we are seeing the activation of something called the NDIS Implementation Plan.

Its official tagline is “Mines to Magnets,” meaning the government isn’t just going to buy a few mines in Nevada and call it a day. It will invest in the entire vertical supply chain.

The U.S. needs to own the mines, the refineries, the processing plants, the chip manufacturers, the energy grid that fuels the AI-driven future…

This is a total retooling of the American economy, reminiscent of the industrial mobilization for WWII. People like JPMorgan (JPM) CEO Jamie Dimon see it coming; that’s why he’s talking about a $1.5 trillion fund for this buildout.

Folks, the government is about to launch the greatest stock buying spree of all time. And I believe they are targeting 119 specific companies to secure our future…

The ‘Cheat Sheet’ for the Next Wave

I’ve been tracking Uncle Sam’s moves for a while. In fact, I recommended MP Materials before the Pentagon bought it; and my subscribers enjoyed the gains. 

Now I’m looking at the next wave of opportunities. The government has tipped its hand, giving a preview of the sectors – and the specific types of stocks – that are next on the ‘buy’ list.

The Hidden Rare Earth Stock Washington Needs

Right now, everyone is looking at Lynas Resources. It’s the obvious play. Gina Rinehart, the richest woman in Australia (and a Mar-a-Lago regular), owns it.

But I’m not buying it. It’s already doubled. It’s listed in Australia. And its processing plant is in Malaysia – too close to China.

Instead, I’ve got my eye on a U.S. company one-eighth the size of Lynas. It’s sitting on the largest deposit of heavy rare-earth elements in the United States – over 1 billion tons.

Better yet, it’s not just digging;  it’s building a magnet manufacturing facility.

This company is the definition of “Mines to Magnets.” Google co-founder Sergey Brin already owns a 7% stake.

And it’s currently trading for around $20 a share.

The Domestic Chip Manufacturer the U.S. Cannot Afford to Lose

We all love AMD (AMD). I recommended it back in 2015… before it went up 13,500%. But AMD doesn’t make chips; it only designs them. Thus, it relies on foreign manufacturing for its supply.

The U.S. government needs a domestic option.

There is a small firm, started by Jerry Sanders – the exact same legend who founded AMD – that actually manufactures chips.

It’s already inked a deal with the Department of War to supply U.S.-made semiconductors for the next 10 years. And it got $1.5 billion from the CHIPS Act.

Recently, the company’s corporate jet was spotted in Florida… rumored to be parked at Mar-a-Lago.

This is the stock the White House has to back to secure the AI supply chain. And it’s about 1/25th the size of AMD and trades for less than $40/share.

The AI Infrastructure Stock Powering America’s Data Centers

Dell (DELL) is a great company. But it’s also a $100 billion behemoth; the ‘easy money’ is long gone. So, I’m looking at another firm instead. 

This one specializes in the critical hardware – liquid cooling and server racks – that keeps AI data centers from melting down. Its revenue is projected to grow 56% next year. And it just built the “Colossus” supercomputer for Elon Musk’s xAI in only 122 days – speed the government loves. 

This company could end up as the crown jewel of the American AI buildout, and it trades for just $50.

Small Modular Reactors and the Coming Energy Bottleneck

This could be the sleeper hit of the decade. 

AI is an ‘energy vampire.’ In fact, a single AI query uses 10x the power of a regular Google search. 

That means that data centers are about to consume more power than many countries; and the grid cannot handle it. Solar and wind are too intermittent. We need baseload power – and the solution lies with nuclear.

But we also can’t wait 10 years for traditional plants to be built… 

Enter Small Modular Reactors (SMRs). They are portable, safe, and can be deployed 80% faster than traditional reactors.

There is one firm leading this race. The current Secretary of Energy was a board member. And the company is already working with the U.S. Air Force to power its Arctic bases.

We see it as the solution to the “Build, Baby, Build” mandate in the government’s AI Action Plan.

The Defense Monopoly at the Center of Naval Expansion

Finally, there’s the ultimate defense play.

America is ramping up production of Columbia-class nuclear submarines and selling them to Australia and the U.K.

There is effectively one company that provides the nuclear reactors and fuel for the U.S. Navy’s entire fleet. It is a virtual monopoly.

If the U.S. is going to project power in the Pacific to counter China, this company’s order book is going to explode. It’s a fraction of the size of the major defense contractors, with big upside potential.

The Window Is Closing

The government is moving fast here – so quickly that stocks are moving on rumors alone. 

Critical Metals Corp (CRML) soared 275% just on a rumor that it was next in line for a cash injection. 

And at one point, United States Antimony (UAMY) was up over 900% this year without a single dollar of government money  – just anticipation.

Now imagine what would happen if a check actually clears…

The government has turned the cash spigot on full blast.

You can try to guess which stocks are on its shopping list, scour 13F filings, and comb through government contract databases… 

Or, you can watch my new briefing, where I break it all down – because I’ve done the legwork so you don’t have to.

I have compiled all my research on 119 companies – including their names, ticker symbols, buy-up-to prices, and the top 5 to buy right now – in a new report all about ‘The President’s ÃÛÌÒ´«Ã½.’

The buying spree has started. Don’t wait until the press release drops. By then, it’s too late.

Watch the presentation and get the list of stocks immediately.

The post Front-Running Federal Investment: The Next Strategic Stocks appeared first on InvestorPlace.

Today, my InvestorPlace colleague Louis Navellier is joining us to explore what the company’s blowout results reveal about where the AI boom is headed next.

With data-center demand still surging, expectations are getting tougher to beat, and the market’s reaction could signal a shift from early hype to the next phase of the AI trade.

This story isn’t just about big revenue – it’s about what comes next.

Take it away, Louis…

In the 1970s, every Sunday morning on CBS’s The NFL Today, a man named “Jimmy the Greek” would sit beside Brent Musburger and calmly predict the final scores of that afternoon’s games.

He never mentioned point spreads. He couldn’t. Sports betting was illegal in most of America.

So instead of talking about the line, he’d say something like, “The Raiders will beat the Rams, 31–21.”

To the average viewer, that sounded like a straightforward prediction.

To anyone who knew the spread, it was something more.

If the Raiders were favored by five and Jimmy predicted a ten-point win, he wasn’t just picking a winner. He was signaling he thought they’d cover the spread. The people paying attention didn’t need him to say the odds out loud. They could read between the lines.

Today, there’s no need for coded language.

Betting is legal across much of the country. In fact, you can wager on everything from the Super Bowl to presidential elections to Taylor Swift’s wedding date.

And increasingly, markets are putting real-time probabilities on corporate events.

This brings us to NVIDIA Corporation (NVDA), which announced earnings after the bell on Wednesday.

For years, I’ve called NVIDIA’s report the grand finale of earnings season. In many ways, it’s like the Super Bowl. Everyone’s watching. And plenty of money is riding on the outcome.

Heading into this quarter, probability markets were assigning better than a 90% chance that NVIDIA would beat earnings.

When confidence gets that high, the question changes. It’s no longer just whether NVIDIA will “win.”

It’s whether it will beat the spread – and by how much.

In other words, if expectations are through the roof, what happens when the bar gets raised so high that even excellence isn’t good enough anymore?

Now, as I’ll explain in a moment, NVIDIA did more than win. By any traditional measure, it was a blowout quarter.

And yet…

As I write this, the stock is down nearly 4% – despite beating on revenue, earnings and guidance.

This is exactly what I predicted in a recent special presentation. I argued that we’re in the middle of an AI Dislocation – a period when market leadership begins to shift. I also warned that expectations for the mega-cap AI stocks had reached extreme levels. And in that kind of environment, even strong results can trigger selling as capital rotates toward new winners. 

So, in today’s issue, I’m going to walk through the details of NVIDIA’s earnings and the market’s subsequent reaction. I’ll also discuss why expectations matter more than the headline numbers… and how moments like this can trigger a sharp rotation in the AI trade – creating risk for the obvious names, and opportunity in the overlooked ones.

The Earnings Scoreboard

Let us start with the facts.

NVIDIA reported earnings of $1.62 per share on revenue of $68.1 billion. Wall Street was expecting $1.53 per share on $65.8 billion in revenue.

That represents revenue growth of 73% compared with the same quarter a year ago.

Data center revenue came in at $62.3 billion, ahead of expectations.

And for the current quarter, the company guided revenue to roughly $78 billion. Analysts had been looking for closer to $72.8 billion.

By any historical standard, those numbers are extraordinary.

I am still amazed that a company of this size can produce accelerating sales and earnings momentum.

And it is not happening in isolation.

Super Micro Computer, Inc. (SMCI) is reporting triple-digit sales growth.

Vertiv Holdings (VRT) is delivering strong sales and guidance.

Taiwan Semiconductor Manufacturing Co. Ltd. (TSM) recently announced January sales growth of 37%, well above its prior guidance of 30%.

In other words, the demand environment across the AI ecosystem remains powerful.

This leads to the question… If the numbers were so strong, why did the stock sell off?

So Why Did the Stock Fall?

There are several reasons.

First, expectations were even higher in some corners of the market. While consensus estimates were around $72.8 billion for the current quarter, some analysts were modeling revenue closer to $80 billion.

When expectations drift that high, even a strong beat can feel like a disappointment relative to the most optimistic projections.

Second, investors are asking tougher questions about sustainability.

Can this level of AI spending continue for years?

Will NVIDIA remain as dominant as artificial intelligence shifts from training massive models to running everyday applications?

Third, there are ongoing uncertainties in China. Licensing approvals remain fluid, and the company is excluding China data center revenue from certain forecasts.

And finally, there is the simple matter of options positioning.

NVIDIA is one of the most actively traded stocks in the world. Many investors write covered calls on the stock. ÃÛÌÒ´«Ã½ makers hedge those positions. When you combine heavy options activity with a company of this size, post-earnings price action can become more mechanical than emotional.

This is what I mean when I told my followers that physics can affect a company of this scale.

It takes enormous capital flows to move the needle.

None of this changes the fact that NVIDIA is still executing at an extremely high level.

The Physics of Expectations

When a company becomes one of the largest in the world, perfection gets priced in.

The bigger the company, the higher the expectations.

And the higher the expectations, the harder it becomes to surprise to the upside in a way that satisfies everyone.

That does not mean the growth story is broken.

It means the bar keeps rising.

NVIDIA’s forward valuation has been compressing because earnings are growing so quickly. That is not the hallmark of a speculative bubble detached from fundamentals.

It is the result of extraordinary profit growth.

Chief Executive Officer Jensen Huang addressed concerns directly on the earnings call. He emphasized that customers are already monetizing their artificial intelligence investments. They are generating real cash flow from the computing capacity they are buying.

This is not speculation without revenue.

This is massive capital deployment backed by visible demand.

But while NVIDIA continues to deliver, something else is happening beneath the surface.

Stage 1 and Stage 2

The AI Dislocation I have been describing is not about the end of the artificial intelligence boom.

It is about leadership rotation within it.

Stage 1 of any technological revolution rewards the obvious leaders. The pioneering companies behind the tech. The headline names. The stocks everyone talks about.

In artificial intelligence, aside from NVIDIA, it’s the mega-cap hyperscalers.

Amazon. Alphabet. Meta. Microsoft.

Collectively, those companies are expected to spend roughly $650 billion on AI-related capital expenditures in 2026 alone.

That level of spending is phenomenal news for the suppliers building out the data center boom.

But for the hyperscalers themselves, it becomes a question of margins and returns. Capital intensity rises. Expectations rise. The bar rises.

Stage 2 is when the companies enabling the buildout begin to show faster earnings acceleration than the giants making the headlines and spending all that money.

In other words, you want to be where the money is flowing.

The power systems. The cooling technology. The semiconductor equipment makers. The networking backbone. The companies NVIDIA and the hyperscalers need to build all those data centers.

These businesses often start from smaller bases. Their revenue growth can compound faster. Their earnings momentum can accelerate more dramatically.

And when capital begins to rotate, the returns for investors can be significant.

The Bottom Line

We are in the middle of an AI Dislocation.

NVIDIA just proved that demand remains strong. The AI boom is not ending. But something is shifting in the market…

Bottom line, I remain very bullish on NVIDIA over the long term. I believe the stock will be significantly higher in the years ahead.

But when expectations for the obvious names reach extreme levels, leadership can shift. And when it does, the biggest percentage gains often come from the companies most investors are not watching.

That is why I recently put together a special briefing detailing what’s going on and how investors can position themselves as this AI Dislocation unfolds.

If you want to position yourself for the next phase of this boom – instead of chasing yesterday’s winners – I strongly encourage you to go here to watch my AI Dislocation briefing now.

Sincerely,

Louis Navellier

Editor, ÃÛÌÒ´«Ã½ 360

The Editor hereby discloses that as of the date of this email, the Editor, directly or indirectly, owns the following securities that are the subject of the commentary, analysis, opinions, advice, or recommendations in, or which are otherwise mentioned in, the essay set forth below:

NVIDIA Corporation (NVDA), Super Micro Computer, Inc. (SMCI) and Vertiv Holdings (VRT)

The post Nvidia’s Earnings Signal a Shift in AI Expectations appeared first on InvestorPlace.

On Wednesday evening, Nvidia Corp. (NVDA) delivered exactly what Wall Street asked for. 

Revenue surged 73% to $68 billion. Data center sales hit a new record. Earnings per share sailed past analyst estimates. By every traditional measure, it was a spectacular quarter. 

And yet, shares fell. 

Louis Navellier has been warning about this for months. Expectations for “Stage 1” artificial intelligence companies building the physical side of AI have become so elevated that even blockbuster results can no longer satisfy them. 

When you’re priced for perfection, perfection isn’t enough. 

That’s why we’ve been eyeing “Stage 2” AI firms. These companies provide the experience of using AI – the products and services that come after the Stage 1 firms have done their job. 

Three weeks ago, I wrote about two of these superstars: Thomson Reuters Corp. (TRI) and ServiceNow Inc. (NOW). These babies had been thrown out with the rest of the Software-as-a-Service (SaaS) bathwater by investors ignoring these firms’ regulatory and data-heavy moats. 

Since then, the two stocks have risen roughly 10%, even as the Nasdaq Composite has fallen. 

This is what our legendary quant analyst, Louis Navellier, has been calling the AI Dislocation. 

But the opportunity isn’t over. If anything, a second wave of indiscriminate selling is now creating an even more compelling entry point for Stage 2 firms. I’ll reveal two of them today.  

Now before I get to them, take a moment to watch Louis’ full AI Dislocation presentation. While I’m focused on the more conservative Stage 2 picks, he’s tracking an entire breakout group with ~500% upside. During that presentation, he shows us why investors are still panic-selling precisely the wrong stocks – and reveals his own top pick for this opportunity. Check it out here. 

Let’s jump in…  

The Town Hall Tech Giant  

In the mid-1990s, a little-known German software firm called SAP began selling its resource-planning systems to large corporations. 

The pitch was simple: Consolidate your payroll, inventory, finance, and human resources systems onto a single platform. Corporations were reluctant at first. Implementation was expensive. Disruptions lasted months. But once a company deployed SAP’s systems, almost no one ever switched. The system became too embedded and too critical to tear out. 

Today, six out of every seven Fortune 500 companies use SAP for their core operations, and SAP is worth $250 billion. 

Tyler Technologies Inc. (TYL) has built essentially the same business… except its customers aren’t Fortune 500 boardrooms. They’re county clerks, school districts, courthouses, and municipalities. 

Since the early 1990s, Tyler has been quietly constructing the digital backbone of local government in America. Its software handles property tax assessments, court case management, utility billing, and municipal financial reporting for thousands of government entities across all 50 states. 

The moat here is extraordinary. 

Consider what it would take for a city to rip out a Tyler-powered property tax system and replace it with a competitor’s product. Town managers would need to convince a risk-averse city council to approve a disruptive multiyear project, and then retrain hundreds of employees and migrate decades of sensitive records. They would also need to hope the new vendor’s rollout goes flawlessly. Because if the tax billing system goes dark, the city’s revenue collection stops. 

This is precisely why municipal governments almost never switch software vendors. Annual customer churn at Tyler sits at just 2%, or half of SAP’s figure. 

Nevertheless, Tyler’s stock has fallen 45% since last year on fears that AI will replace its business. These concerns were compounded by recent plug-in launches around Anthropic’s Claude Code. As I noted three weeks ago, shares of Thomson Reuters, too, plummeted after Anthropic added a legal plug-in that can review contracts and more.  

I find these issues completely overblown.  

Municipal governments are not in the business of creating their own software, and barriers to new entrants are high. Unlike Fortune 500 companies, local governments are institutionally allergic to risk. Their job is to keep the lights on and the trash collected, not to experiment with new software vendors. 

In fact, the development of AI should help Tyler sell more products. The company already uses AI solutions to help automate repetitive administration tasks, run customer-facing chatbots, predict infrastructure outages, and allocate resources. Better AI will only make these products more desirable. Tyler’s management believes they could eventually sell 8-10 products per customer, up from around three today. 

Then there’s another signal here that I find impossible to ignore: 

Insiders are buying. 

Over the past week, we’ve seen: 

• Director. Purchased 1,600 shares 
• Chief Administrative Officer (CAO). Purchased 610 shares 

These are genuinely meaningful purchases at current $350-per-share prices. In fact, the CAO’s purchase doubled her stake in the company. 

Finally, it’s worth noting that Tyler’s No. 1 market position still gives it only a 6% share of the fragmented public-sector software market. There’s plenty of room for Tyler to keep nibbling away at local governments that are finally ready to throw out their aging, decades-old IT systems for a more modern solution that includes AI capabilities. 

According to my models, an extremely conservative 3% long-term growth rate gives Tyler a target price of $500… a 49% upside from here. And if long-term growth is closer to 6%, as I expect, Tyler would prove to be a multi-bagger Stage 2 AI firm hiding right at your local town hall. 

The Cybersecurity Firm That AI Can’t Replace 

Earlier last week, a new wave of fear swept through the cybersecurity sector. The worry wasn’t about a new type of attack or a high-profile breach. 

It was about AI itself, specifically Anthropic’s latest cybersecurity plug-in. 

In a blog post, the AI firm revealed how Claude Code Security can now scan codebases for security vulnerabilities and suggest software patches for human review. Anthropic has already used the system to detect real-world coding flaws.  

Here’s from the company’s blog post: 

Using Claude Opus 4.6, released earlier this month, our team found over 500 vulnerabilities in production open-source codebases—bugs that had gone undetected for decades, despite years of expert review. We’re working through triage and responsible disclosure with maintainers now, and we plan to expand our security work with the open-source community. 

Now, I agree that Claude Code will disrupt many cybersecurity firms, especially the ones built to scan code for errors. Firms offering “DevSecOps” tools, like GitLab Inc. (GTLB) and Palo Alto Networks Inc. (PANW), will see slices of their businesses disappear due to this new technology. 

However, AI is inherently limited to the data it’s trained on. 

It doesn’t have access to the real-time data that’s created every day by new attacks… 

And it doesn’t have the ability to compete against Zscaler Inc. (ZS), the global pioneer (and current leader) in zero-trust security solutions. 

As a quick primer: Zero-trust systems are a cybersecurity approach that constantly verifies every user and every device. It’s a monitoring system that’s watching every connection in and out of a company’s systems. In addition, if a password is stolen or a device is breached, Zscaler’s systems are designed to limit access to reduce the harm.  

In other words, Zscaler’s business is not a problem you solve or a bug you fix. It’s an arms race. New attack vectors emerge constantly, and the only way to reliably defend against bad actors is to know what those attacks look like in the wild. 

That’s where data comes in. Zscaler sits at the center of a vast global security network that processes billions of events every single day. The company’s platform handles traffic for tens of thousands of enterprise customers, which means it has accumulated petabytes of real-world threat intelligence that no AI model trained on publicly available code can come close to replicating. When a new ransomware variant strikes a hospital in Munich, Zscaler sees it. When a state-sponsored actor tests a new phishing technique against a bank in Singapore, Zscaler sees that, too. 

Of course, artificial intelligence will someday create a competing zero-trust product. But whatever platform it builds will look much like what’s already in the market… and ZS has plenty of experience competing against both larger and smaller rivals from Cisco Systems Inc. (CSCO) to Check Point Software Technologies Ltd. (CHKP). 

In other words, Zscaler’s “secret sauce” is not about writing code cheaply or detecting errors in programs. (In fact, ZS’s recent acquisitions suggest it already uses AI in its workflows.) 

It’s about creating a polished product that can absorb enormous amounts of data, convert them into actions, react to new threats, and have people come and help customers when things go wrong. AI can supplement this business, but not replace it. 

It’s also noteworthy that artificial intelligence will actually increase demand for Zscaler’s products. The technology opens new ways for bad actors to gain unauthorized access to company systems – from tricking users with deepfake videos to automating vulnerability discovery. Each of these new pathways will require new zero-trust tools to mitigate. 

Just last week, a hacker exploited Anthropic’s own AI tools to carry out a series of attacks against Mexican government agencies. One hundred and fifty gigabytes of sensitive documents were stolen, including taxpayer records, voter information, and government employee credentials. These are the attacks Zscaler is designed to mitigate. 

My models put ZS’ current value at $260 per share, a 60% upside from today’s levels. And if AI triggers a stampede of demand, we could see ZS rise 100% or more from here. 

We’ve Seen This Movie Before 

In March 2000, Cisco became the most valuable company in the world. It was the picks-and-shovels play of the internet boom, building the routers and switches that the whole digital revolution relied on. Investors couldn’t get enough. 

Eighteen months later, Cisco had lost 85% of its value. 

Meanwhile, a separate set of companies used the internet to build lasting fortunes.  

• Boring winners. Some were quieter names. Salesforce Inc. (CRM) and SAP SE (SAP) operated in the background, content with grinding higher through embedding themselves in Fortune 500 companies 
• Growth winners. Others were flashier growth companies. Alphabet Inc. (GOOGL) and Amazon.com Inc. (AMZN) used the internet to turn into breakout success stories. Netflix Inc. (NFLX) turned every $10,000 invested into $7.7 million. 

You already know where I’m going with this. 

Today, artificial intelligence is approaching its own Cisco moment. Initial Stage 1 winners are now valued so richly that even perfect execution is no longer enough. 

Meanwhile, an entire new cohort of Stage 2 companies are ready to rise. 

I’ve now given you four of these “boring winners” that should grind higher over time. TRI, NOW, TYL, and ZS are all conservative picks that benefit from improving AI. 

But what about the growth winners? The companies that can rise 500% or more? 

Louis Navellier has identified a specific group that he believes still offers enormous multi-bagger upside. His full presentation explains exactly why… and gives you one specific name to buy. 

Watch Louis Navellier’s AI Dislocation presentation here. 

Until next week, 

Thomas Yeung, CFA 

ÃÛÌÒ´«Ã½ Analyst, InvestorPlace 

Thomas Yeung is a market analyst and portfolio manager of the Omnia Portfolio, the highest-tier subscription at InvestorPlace. He is the former editor of Tom Yeung’s Profit & Protection, a free e-letter about investing to profit in good times and protecting gains during the bad.

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